ci : reduce PR jobs by matching backend paths (#23675)

* ci : disable SYCL f16 builds

* ci : extract android and hip into separate workflows

* ci : move webgpu to separate workflow

* ci : move the rpc to a separate workflow

* ci : extract s309x and ppcl jobs

* ci : extract opencl job into a separate workflow

.devops/cann.Dockerfile

@@ -5,6 +5,9 @@
 # Define the CANN base image for easier version updates later
 ARG CHIP_TYPE=910b
 ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.5.0-${CHIP_TYPE}-openeuler24.03-py3.11
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 # ==============================================================================
 # BUILD STAGE
@@ -55,6 +58,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full && \
     cp build/bin/* /app/full/ && \
     cp *.py /app/full/ && \
+    cp -r conversion /app/full/ && \
     cp -r gguf-py /app/full/ && \
     cp -r requirements /app/full/ && \
     cp requirements.txt /app/full/
@@ -67,6 +71,19 @@ RUN mkdir -p /app/full && \
 # ==============================================================================
 FROM ${CANN_BASE_IMAGE} AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 # -- Install runtime dependencies --
 RUN yum install -y libgomp curl && \
     yum clean all && \

.devops/cpu.Dockerfile

@@ -1,4 +1,7 @@
 ARG UBUNTU_VERSION=24.04
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 FROM ubuntu:$UBUNTU_VERSION AS build
 
@@ -27,6 +30,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -35,6 +39,19 @@ RUN mkdir -p /app/full \
 ## Base image
 FROM ubuntu:$UBUNTU_VERSION AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN apt-get update \
     && apt-get install -y libgomp1 curl \
     && apt autoremove -y \

.devops/cuda.Dockerfile

@@ -6,6 +6,10 @@ ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VER
 
 ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+
 FROM ${BASE_CUDA_DEV_CONTAINER} AS build
 
 # CUDA architecture to build for (defaults to all supported archs)
@@ -32,6 +36,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -40,6 +45,19 @@ RUN mkdir -p /app/full \
 ## Base image
 FROM ${BASE_CUDA_RUN_CONTAINER} AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN apt-get update \
     && apt-get install -y libgomp1 curl \
     && apt autoremove -y \

.devops/intel.Dockerfile

@@ -1,12 +1,22 @@
 ARG ONEAPI_VERSION=2025.3.3-0-devel-ubuntu24.04
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 ## Build Image
 
 FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS build
 
 ARG GGML_SYCL_F16=OFF
+ARG LEVEL_ZERO_VERSION=1.28.2
+ARG LEVEL_ZERO_UBUNTU_VERSION=u24.04
 RUN apt-get update && \
-    apt-get install -y git libssl-dev
+    apt-get install -y git libssl-dev wget ca-certificates && \
+    cd /tmp && \
+    wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero.deb && \
+    wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb && \
+    apt-get -o Dpkg::Options::="--force-overwrite" install -y ./level-zero.deb ./level-zero-devel.deb && \
+    rm -f /tmp/level-zero.deb /tmp/level-zero-devel.deb
 
 WORKDIR /app
 
@@ -26,6 +36,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -33,11 +44,24 @@ RUN mkdir -p /app/full \
 
 FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS base
 
-ARG IGC_VERSION=v2.30.1
-ARG IGC_VERSION_FULL=2_2.30.1+20950
-ARG COMPUTE_RUNTIME_VERSION=26.09.37435.1
-ARG COMPUTE_RUNTIME_VERSION_FULL=26.09.37435.1-0
-ARG IGDGMM_VERSION=22.9.0
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
+ARG IGC_VERSION=v2.20.5
+ARG IGC_VERSION_FULL=2_2.20.5+19972
+ARG COMPUTE_RUNTIME_VERSION=25.40.35563.10
+ARG COMPUTE_RUNTIME_VERSION_FULL=25.40.35563.10-0
+ARG IGDGMM_VERSION=22.8.2
 RUN mkdir /tmp/neo/ && cd /tmp/neo/ \
   && wget https://github.com/intel/intel-graphics-compiler/releases/download/$IGC_VERSION/intel-igc-core-${IGC_VERSION_FULL}_amd64.deb \
   && wget https://github.com/intel/intel-graphics-compiler/releases/download/$IGC_VERSION/intel-igc-opencl-${IGC_VERSION_FULL}_amd64.deb \
@@ -109,4 +133,3 @@ WORKDIR /app
 HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
 
 ENTRYPOINT [ "/app/llama-server" ]
-

.devops/llama-cli-cann.Dockerfile

@@ -1,4 +1,7 @@
 ARG ASCEND_VERSION=8.5.0-910b-openeuler22.03-py3.10
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 FROM ascendai/cann:$ASCEND_VERSION AS build
 
@@ -28,6 +31,20 @@ RUN echo "Building with static libs" && \
 
 # TODO: use image with NNRT
 FROM ascendai/cann:$ASCEND_VERSION AS runtime
+
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 COPY --from=build /app/build/bin/llama-cli /app/build/bin/llama-completion /
 
 ENV LC_ALL=C.utf8

.devops/musa.Dockerfile

@@ -6,6 +6,10 @@ ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_V
 
 ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}-amd64
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+
 FROM ${BASE_MUSA_DEV_CONTAINER} AS build
 
 # MUSA architecture to build for (defaults to all supported archs)
@@ -37,6 +41,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -45,6 +50,19 @@ RUN mkdir -p /app/full \
 ## Base image
 FROM ${BASE_MUSA_RUN_CONTAINER} AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN apt-get update \
     && apt-get install -y libgomp1 curl \
     && apt autoremove -y \

.devops/nix/package.nix

@@ -103,6 +103,7 @@ let
     vulkan-headers
     vulkan-loader
     shaderc
+    spirv-headers
   ];
 in
 
@@ -146,7 +147,6 @@ effectiveStdenv.mkDerivation (finalAttrs: {
       ninja
       pkg-config
       git
-      spirv-headers
     ]
     ++ optionals useCuda [
       cudaPackages.cuda_nvcc

.devops/openvino.Dockerfile

@@ -18,6 +18,10 @@ ARG LIBZE1_VERSION=1.27.0-1~24.04~ppa2
 ARG http_proxy=
 ARG https_proxy=
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+
 ## Build Image
 FROM ubuntu:${UBUNTU_VERSION} AS build
 
@@ -77,6 +81,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/ReleaseOV/bin/* /app/full/ \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -88,6 +93,18 @@ FROM ubuntu:${UBUNTU_VERSION} AS base
 # Pass proxy args to runtime stage
 ARG http_proxy
 ARG https_proxy
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
 
 RUN apt-get update \
     && apt-get install -y libgomp1 libtbb12 curl wget ocl-icd-libopencl1 \

.devops/rocm.Dockerfile

@@ -7,6 +7,10 @@ ARG AMDGPU_VERSION=7.2.1
 # Target the ROCm build image
 ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+
 ### Build image
 FROM ${BASE_ROCM_DEV_CONTAINER} AS build
 
@@ -49,6 +53,7 @@ RUN mkdir -p /app/lib \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -57,6 +62,19 @@ RUN mkdir -p /app/full \
 ## Base image
 FROM ${BASE_ROCM_DEV_CONTAINER} AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN apt-get update \
     && apt-get install -y libgomp1 curl \
     && apt autoremove -y \

.devops/s390x.Dockerfile

@@ -1,5 +1,8 @@
 ARG GCC_VERSION=15.2.0
 ARG UBUNTU_VERSION=24.04
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 ### Build Llama.cpp stage
 FROM gcc:${GCC_VERSION} AS build
@@ -34,6 +37,7 @@ RUN --mount=type=cache,target=/root/.ccache \
 
 COPY *.py             /opt/llama.cpp/bin
 COPY .devops/tools.sh /opt/llama.cpp/bin
+COPY conversion       /opt/llama.cpp/conversion
 
 COPY gguf-py          /opt/llama.cpp/gguf-py
 COPY requirements.txt /opt/llama.cpp/gguf-py
@@ -44,14 +48,28 @@ COPY requirements     /opt/llama.cpp/gguf-py/requirements
 FROM scratch AS collector
 
 # Copy llama.cpp binaries and libraries
-COPY --from=build /opt/llama.cpp/bin     /llama.cpp/bin
-COPY --from=build /opt/llama.cpp/lib     /llama.cpp/lib
-COPY --from=build /opt/llama.cpp/gguf-py /llama.cpp/gguf-py
+COPY --from=build /opt/llama.cpp/bin        /llama.cpp/bin
+COPY --from=build /opt/llama.cpp/lib        /llama.cpp/lib
+COPY --from=build /opt/llama.cpp/gguf-py    /llama.cpp/gguf-py
+COPY --from=build /opt/llama.cpp/conversion /llama.cpp/conversion
 
 
 ### Base image
 FROM ubuntu:${UBUNTU_VERSION} AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
     --mount=type=cache,target=/var/lib/apt/lists,sharing=locked \
     apt update -y && \
@@ -91,6 +109,7 @@ RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
 
 COPY --from=collector /llama.cpp/bin /app
 COPY --from=collector /llama.cpp/gguf-py /app/gguf-py
+COPY --from=collector /llama.cpp/conversion /app/conversion
 
 RUN pip install --no-cache-dir --break-system-packages \
         -r /app/gguf-py/requirements.txt

.devops/vulkan.Dockerfile

@@ -1,4 +1,7 @@
 ARG UBUNTU_VERSION=26.04
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
 
 FROM ubuntu:$UBUNTU_VERSION AS build
 
@@ -23,6 +26,7 @@ RUN mkdir -p /app/lib && \
 RUN mkdir -p /app/full \
     && cp build/bin/* /app/full \
     && cp *.py /app/full \
+    && cp -r conversion /app/full \
     && cp -r gguf-py /app/full \
     && cp -r requirements /app/full \
     && cp requirements.txt /app/full \
@@ -31,6 +35,19 @@ RUN mkdir -p /app/full \
 ## Base image
 FROM ubuntu:$UBUNTU_VERSION AS base
 
+ARG BUILD_DATE=N/A
+ARG APP_VERSION=N/A
+ARG APP_REVISION=N/A
+ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
+ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
+LABEL org.opencontainers.image.created=$BUILD_DATE \
+      org.opencontainers.image.version=$APP_VERSION \
+      org.opencontainers.image.revision=$APP_REVISION \
+      org.opencontainers.image.title="llama.cpp" \
+      org.opencontainers.image.description="LLM inference in C/C++" \
+      org.opencontainers.image.url=$IMAGE_URL \
+      org.opencontainers.image.source=$IMAGE_SOURCE
+
 RUN apt-get update \
     && apt-get install -y libgomp1 curl libvulkan1 mesa-vulkan-drivers \
     libglvnd0 libgl1 libglx0 libegl1 libgles2 \

.editorconfig

@@ -45,15 +45,7 @@ insert_final_newline = unset
 trim_trailing_whitespace = unset
 insert_final_newline = unset
 
-[tools/server/webui/**]
-indent_style = unset
-indent_size = unset
-end_of_line = unset
-charset = unset
-trim_trailing_whitespace = unset
-insert_final_newline = unset
-
-[tools/server/public/**]
+[tools/ui/**]
 indent_style = unset
 indent_size = unset
 end_of_line = unset

.gitattributes

@@ -1,4 +0,0 @@
-# Treat the generated single-file WebUI build as binary for diff purposes.
-# Git's pack-file delta compression still works (byte-level), but this prevents
-# git diff from printing the entire minified file on every change.
-tools/server/public/index.html -diff

.github/ISSUE_TEMPLATE/010-bug-compilation.yml

@@ -12,6 +12,8 @@ body:
         after recreating the CMake build directory and with `-DGGML_CCACHE=OFF`.
         If the compilation succeeds with ccache disabled you should be able to permanently fix the issue
         by clearing `~/.cache/ccache` (on Linux).
+
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
   - type: textarea
     id: commit
     attributes:

.github/ISSUE_TEMPLATE/011-bug-results.yml

@@ -1,5 +1,5 @@
 name: Bug (model use)
-description: Something goes wrong when using a model (in general, not specific to a single llama.cpp module).
+description: Something goes wrong when running a model (crashes, garbled outputs, etc.).
 title: "Eval bug: "
 labels: ["bug-unconfirmed", "model evaluation"]
 body:
@@ -12,6 +12,8 @@ body:
         If you encountered the issue while using an external UI (e.g. ollama),
         please reproduce your issue using one of the examples/binaries in this repository.
         The `llama-completion` binary can be used for simple and reproducible model inference.
+
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
   - type: textarea
     id: version
     attributes:
@@ -98,8 +100,8 @@ body:
       label: Relevant log output
       description: >
           Please copy and paste any relevant log output, including the command that you entered and any generated text.
-          For very long logs (thousands of lines), preferably upload them as files instead.
-          On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
+          For very long logs (thousands of lines), please upload them as files instead; the `--log-file` CLI argument can be used for this purpose.
+          On Linux you can alternatively redirect the console output of any command into a file by appending ` > llama.log 2>&1` to your command.
       value: |
         <details>
         <summary>Logs</summary>

.github/ISSUE_TEMPLATE/019-bug-misc.yml

@@ -10,6 +10,8 @@ body:
         This issue template is intended for miscellaneous bugs that don't fit into any other category.
         If you encountered the issue while using an external UI (e.g. ollama),
         please reproduce your issue using one of the examples/binaries in this repository.
+
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
   - type: textarea
     id: version
     attributes:
@@ -86,8 +88,8 @@ body:
       description: >
           If applicable, please copy and paste any relevant log output, including any generated text.
           If you are encountering problems specifically with the `llama_params_fit` module, always upload `--verbose` logs as well.
-          For very long logs (thousands of lines), please upload them as files instead.
-          On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
+          For very long logs (thousands of lines), please upload them as files instead; the `--log-file` CLI argument can be used for this purpose.
+          On Linux you can alternatively redirect the console output of any command into a file by appending ` > llama.log 2>&1` to your command.
       value: |
         <details>
         <summary>Logs</summary>

.github/ISSUE_TEMPLATE/020-enhancement.yml

@@ -8,6 +8,8 @@ body:
       value: |
         [Please post your idea first in Discussion if there is not yet a consensus for this enhancement request. This will help to keep this issue tracker focused on enhancements that the community has agreed needs to be implemented.](https://github.com/ggml-org/llama.cpp/discussions/categories/ideas)
 
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
+
   - type: checkboxes
     id: prerequisites
     attributes:

.github/ISSUE_TEMPLATE/030-research.yml

@@ -8,6 +8,8 @@ body:
       value: |
         Don't forget to check for any [duplicate research issue tickets](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3A%22research+%F0%9F%94%AC%22)
 
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
+
   - type: checkboxes
     id: research-stage
     attributes:

.github/ISSUE_TEMPLATE/040-refactor.yml

@@ -9,6 +9,8 @@ body:
         Don't forget to [check for existing refactor issue tickets](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3Arefactoring) in case it's already covered.
         Also you may want to check [Pull request refactor label as well](https://github.com/ggml-org/llama.cpp/pulls?q=is%3Aopen+is%3Apr+label%3Arefactoring) for duplicates too.
 
+        Please fill out this template yourself, copypasting language model outputs is [strictly prohibited](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md#ai-usage-policy).
+
   - type: textarea
     id: background-description
     attributes:

.github/actions/linux-setup-spacemit/action.yml

@@ -15,6 +15,6 @@ runs:
       id: setup
       uses: ./.github/actions/unarchive-tar
       with:
-        url: https://archive.spacemit.com/toolchain/spacemit-toolchain-linux-glibc-x86_64-v${{ inputs.version }}.tar.xz
+        url: https://github.com/spacemit-com/toolchain/releases/download/v${{ inputs.version }}/spacemit-toolchain-linux-glibc-x86_64-v${{ inputs.version }}.tar.xz
         path: ${{ inputs.path }}
         strip: 1

.github/actions/unarchive-tar/action.yml

@@ -24,4 +24,4 @@ runs:
       run: |
         mkdir -p ${{ inputs.path }}
         cd ${{ inputs.path }}
-        curl --no-progress-meter ${{ inputs.url }} | tar -${{ inputs.type }}x --strip-components=${{ inputs.strip }}
+        curl --no-progress-meter -L ${{ inputs.url }} | tar -${{ inputs.type }}x --strip-components=${{ inputs.strip }}

.github/labeler.yml

@@ -73,11 +73,10 @@ android:
     - changed-files:
         - any-glob-to-any-file:
             - examples/llama.android/**
-server/webui:
+server/ui:
     - changed-files:
         - any-glob-to-any-file:
-            - tools/server/webui/**
-            - tools/server/public/**
+            - tools/ui/**
 server:
     - changed-files:
         - any-glob-to-any-file:

.github/workflows/build-and-test-snapdragon.yml

@@ -31,7 +31,7 @@ jobs:
   android-ndk-snapdragon:
     runs-on: ubuntu-latest
     container:
-      image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.3'
+      image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.6'
     defaults:
       run:
         shell: bash
@@ -58,14 +58,45 @@ jobs:
           name: llama-cpp-android-arm64-snapdragon
           path: pkg-snapdragon/llama.cpp
 
+  linux-iot-snapdragon:
+    runs-on: ubuntu-latest
+    container:
+      image: 'ghcr.io/snapdragon-toolchain/arm64-linux:v0.6'
+    defaults:
+      run:
+        shell: bash
+
+    steps:
+      - name: Clone
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          lfs: false
+
+      - name: Build Llama.CPP for Snapdragon Linux IoT
+        id: build_llama_cpp_snapdragon_linux
+        run: |
+          cp docs/backend/snapdragon/CMakeUserPresets.json .
+          cmake --preset arm64-linux-snapdragon-release -B build-snapdragon -DGGML_OPENCL=ON
+          cmake --build build-snapdragon -j $(nproc)
+          cmake --install build-snapdragon --prefix pkg-snapdragon/llama.cpp
+
+      - name: Upload Llama.CPP Snapdragon Linux IoT Build Artifact
+        if: ${{ always() && steps.build_llama_cpp_snapdragon_linux.outcome == 'success' }}
+        uses: actions/upload-artifact@v6
+        with:
+          name: llama-cpp-linux-arm64-snapdragon
+          path: pkg-snapdragon/llama.cpp
+
   test-snapdragon-qdc:
-    name: Test on QDC Android Device (${{ matrix.device }})
-    needs: [android-ndk-snapdragon]
-    runs-on: ubuntu-slim
+    name: Test on QDC Device (${{ matrix.device }})
+    needs: [android-ndk-snapdragon, linux-iot-snapdragon]
+    runs-on: ubuntu-24.04-arm
+    timeout-minutes: 90
     strategy:
       fail-fast: false
       matrix:
-        device: [SM8750, SM8650, SM8850]
+        device: [SM8750, SM8850, QCS9075M]
 
     steps:
       - name: Checkout
@@ -74,11 +105,11 @@ jobs:
       - name: Download build artifact
         uses: actions/download-artifact@v7
         with:
-          name: llama-cpp-android-arm64-snapdragon
+          name: ${{ startsWith(matrix.device, 'QCS') && 'llama-cpp-linux-arm64-snapdragon' || 'llama-cpp-android-arm64-snapdragon' }}
           path: pkg-snapdragon/llama.cpp
 
       - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: '3.x'
           cache: pip
@@ -107,7 +138,8 @@ jobs:
               --test       all \
               --pkg-dir    pkg-snapdragon/llama.cpp \
               --model-url  "https://huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF/resolve/main/Llama-3.2-1B-Instruct-Q4_0.gguf" \
-              --device     ${{ matrix.device }}
+              --device     ${{ matrix.device }} \
+              ${{ startsWith(matrix.device, 'QCS') && '--retries 2 --retry-delay 300' || '' }}
         env:
           QDC_API_KEY: ${{ secrets.QDC_API_KEY }}
 

.github/workflows/build-android.yml

@@ -73,6 +73,11 @@ jobs:
           fetch-depth: 0
           lfs: false
 
+      - name: Dependencies
+        run: |
+          apt-get update
+          apt-get install -y build-essential
+
       - name: Build
         id: ndk_build
         run: |
@@ -86,3 +91,53 @@ jobs:
         with:
           name: llama-cpp-android-arm64-cpu
           path: pkg-adb/llama.cpp
+
+  android-arm64:
+    runs-on: ubuntu-latest
+
+    env:
+      NDK_VERSION: "29.0.14206865"
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: android-arm64
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Set up JDK
+        uses: actions/setup-java@v5
+        with:
+          java-version: 17
+          distribution: temurin
+
+      - name: Setup Android SDK
+        uses: android-actions/setup-android@40fd30fb8d7440372e1316f5d1809ec01dcd3699 # v4.0.1
+        with:
+          log-accepted-android-sdk-licenses: false
+
+      - name: Install NDK
+        run: |
+          sdkmanager "ndk;${{ env.NDK_VERSION }}"
+          echo "ANDROID_NDK=${ANDROID_SDK_ROOT}/ndk/${{ env.NDK_VERSION }}" >> $GITHUB_ENV
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DCMAKE_TOOLCHAIN_FILE=${ANDROID_NDK}/build/cmake/android.toolchain.cmake \
+            -DANDROID_ABI=arm64-v8a \
+            -DANDROID_PLATFORM=android-28 \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            -DGGML_BACKEND_DL=ON \
+            -DGGML_NATIVE=OFF \
+            -DGGML_CPU_ALL_VARIANTS=ON \
+            -DGGML_OPENMP=OFF \
+            -DLLAMA_BUILD_BORINGSSL=ON \
+            -DGGML_RPC=ON
+          time cmake --build build --config Release -j $(nproc)

.github/workflows/build-apple.yml

@@ -59,6 +59,7 @@ jobs:
           cmake -B build -G Xcode \
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_COMMON=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
@@ -89,6 +90,7 @@ jobs:
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
             -DLLAMA_OPENSSL=OFF \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
             -DLLAMA_BUILD_TESTS=OFF \
@@ -138,6 +140,7 @@ jobs:
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
             -DLLAMA_BUILD_COMMON=OFF \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
             -DLLAMA_BUILD_TESTS=OFF \
@@ -163,6 +166,7 @@ jobs:
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
             -DLLAMA_BUILD_COMMON=OFF \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
             -DLLAMA_BUILD_TESTS=OFF \
@@ -206,6 +210,7 @@ jobs:
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
             -DLLAMA_OPENSSL=OFF \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
             -DLLAMA_BUILD_TESTS=OFF \

.github/workflows/build-cmake-pkg.yml

@@ -5,23 +5,23 @@ on:
 
 jobs:
   linux:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, Linux, CPU]
     steps:
       - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - name: Install dependencies
-        run: |
-          sudo apt update
-          sudo apt install -y build-essential tcl cmake
-
       - name: Build
         run: |
           PREFIX="$(pwd)"/inst
-          cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX" \
-                -DLLAMA_OPENSSL=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=OFF \
-                -DLLAMA_BUILD_EXAMPLES=OFF -DCMAKE_BUILD_TYPE=Release
+          cmake -S . -B build \
+                -DCMAKE_PREFIX_PATH="$PREFIX" \
+                -DLLAMA_OPENSSL=OFF \
+                -DLLAMA_BUILD_TESTS=OFF \
+                -DLLAMA_BUILD_TOOLS=OFF \
+                -DLLAMA_BUILD_EXAMPLES=OFF \
+                -DLLAMA_BUILD_APP=OFF \
+                -DCMAKE_BUILD_TYPE=Release
           cmake --build build --config Release
           cmake --install build --prefix "$PREFIX" --config Release
 

.github/workflows/build-cross.yml

@@ -277,7 +277,7 @@ jobs:
 
     env:
       # Make sure this is in sync with build-cache.yml
-      SPACEMIT_IME_TOOLCHAIN_VERSION: "1.1.2"
+      SPACEMIT_IME_TOOLCHAIN_VERSION: "1.2.4"
 
     steps:
       - uses: actions/checkout@v6
@@ -301,16 +301,17 @@ jobs:
           export RISCV_ROOT_PATH=${PWD}/spacemit_toolchain
           cmake -B build -DLLAMA_OPENSSL=OFF \
                          -DCMAKE_BUILD_TYPE=Release \
-                         -DGGML_OPENMP=OFF \
                          -DLLAMA_BUILD_EXAMPLES=ON \
+                         -DGGML_CPU_REPACK=OFF \
                          -DLLAMA_BUILD_TOOLS=ON \
                          -DLLAMA_BUILD_TESTS=OFF \
                          -DGGML_CPU_RISCV64_SPACEMIT=ON \
                          -DGGML_RVV=ON \
+                         -DGGML_RV_ZVFH=ON \
                          -DGGML_RV_ZFH=ON \
                          -DGGML_RV_ZICBOP=ON \
                          -DGGML_RV_ZIHINTPAUSE=ON \
-                         -DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 \
+                         -DGGML_RV_ZBA=ON \
                          -DCMAKE_TOOLCHAIN_FILE=${PWD}/cmake/riscv64-spacemit-linux-gnu-gcc.cmake
 
           cmake --build build --config Release -j $(nproc)

.github/workflows/build-hip.yml

@@ -0,0 +1,167 @@
+name: CI (hip)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-hip.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp',
+      '**/*.cu',
+      '**/*.cuh'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-hip.yml',
+      'ggml/src/ggml-cuda/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  GGML_NLOOP: 3
+  GGML_N_THREADS: 1
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+
+jobs:
+
+  ubuntu-22-hip:
+    runs-on: ubuntu-22.04
+    container: rocm/dev-ubuntu-22.04:6.1.2
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev rocwmma-dev
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: ubuntu-22-hip
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Build with native CMake HIP support
+        id: cmake_build
+        run: |
+          cmake -B build -S . \
+            -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
+            -DGGML_HIP_ROCWMMA_FATTN=ON \
+            -DGPU_TARGETS="gfx1030" \
+            -DGGML_HIP=ON
+          cmake --build build --config Release -j $(nproc)
+
+  windows-latest-hip:
+    runs-on: windows-2022
+
+    env:
+      # Make sure this is in sync with build-cache.yml
+      HIPSDK_INSTALLER_VERSION: "26.Q1"
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Grab rocWMMA package
+        id: grab_rocwmma
+        run: |
+          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70201-81~24.04_amd64.deb"
+          7z x rocwmma.deb
+          7z x data.tar
+
+      - name: Use ROCm Installation Cache
+        uses: actions/cache@v5
+        id: cache-rocm
+        with:
+          path: C:\Program Files\AMD\ROCm
+          key: rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
+
+      - name: Setup ROCm
+        if: steps.cache-rocm.outputs.cache-hit != 'true'
+        uses: ./.github/actions/windows-setup-rocm
+        with:
+          version: ${{ env.HIPSDK_INSTALLER_VERSION }}
+
+      - name: Verify ROCm
+        id: verify
+        run: |
+          # Find and test ROCm installation
+          $clangPath = Get-ChildItem 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | Select-Object -First 1
+          if (-not $clangPath) {
+            Write-Error "ROCm installation not found"
+            exit 1
+          }
+          & $clangPath.FullName --version
+
+      - name: Install ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: ${{ github.job }}
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Build
+        id: cmake_build
+        run: |
+          $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
+          $env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
+          cmake -G "Unix Makefiles" -B build -S . `
+            -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
+            -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
+            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.1/include/" `
+            -DCMAKE_BUILD_TYPE=Release `
+            -DLLAMA_BUILD_BORINGSSL=ON `
+            -DROCM_DIR="${env:HIP_PATH}" `
+            -DGGML_HIP=ON `
+            -DGGML_HIP_ROCWMMA_FATTN=ON `
+            -DGPU_TARGETS="gfx1100"  `
+            -DGGML_RPC=ON
+          cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
+
+  ubuntu-22-musa:
+    runs-on: ubuntu-22.04
+    container: mthreads/musa:rc4.3.0-devel-ubuntu22.04-amd64
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Dependencies
+        id: depends
+        run: |
+          apt-get update
+          apt-get install -y build-essential git cmake libssl-dev
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: ubuntu-22-musa
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Build with native CMake MUSA support
+        id: cmake_build
+        run: |
+          cmake -B build -S . \
+            -DGGML_MUSA=ON
+          time cmake --build build --config Release -j $(nproc)

.github/workflows/build-ibm.yml

@@ -0,0 +1,150 @@
+name: CI (ibm)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-ibm.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-ibm.yml',
+      'ggml/src/ggml-cpu/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  GGML_NLOOP: 3
+  GGML_N_THREADS: 1
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+
+jobs:
+
+  ubuntu-24-s390x:
+    runs-on: ubuntu-24.04-s390x
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Build Dependencies
+        id: build_depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y --no-install-recommends \
+            python3 python3-pip python3-dev python3-wheel \
+            libjpeg-dev build-essential libssl-dev \
+            git-lfs
+
+      - name: Toolchain workaround (GCC 14)
+        run: |
+          sudo apt-get install -y gcc-14 g++-14
+          echo "CC=gcc-14" >> "$GITHUB_ENV"
+          echo "CXX=g++-14" >> "$GITHUB_ENV"
+
+      - name: Python Dependencies
+        id: python_depends
+        run: |
+          export PIP_BREAK_SYSTEM_PACKAGES="1"
+          python3 -m pip install --upgrade pip setuptools
+          pip3 install ./gguf-py
+
+      - name: Swap Endianness
+        id: endianness
+        run: |
+          for f in models/*.gguf; do
+            echo YES | python3 gguf-py/gguf/scripts/gguf_convert_endian.py $f big
+          done
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            -DGGML_RPC=ON
+          time cmake --build build --config Release -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose --timeout 900
+
+      - name: Test llama2c (s390x)
+        id: llama2c_test_s390x
+        run: |
+          cd build
+          echo "Fetch llama2c big-endian model"
+          wget https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K-be.gguf
+          ./bin/llama-completion -m stories260K-be.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+
+  ubuntu-24-ppc64le:
+    runs-on: ubuntu-24.04-ppc64le
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Build Dependencies
+        id: build_depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y --no-install-recommends \
+            python3 python3-pip python3-dev python3-wheel \
+            libjpeg-dev build-essential libssl-dev \
+            git-lfs
+
+      - name: Toolchain workaround (GCC 14)
+        run: |
+          sudo apt-get install -y gcc-14 g++-14
+          echo "CC=gcc-14" >> "$GITHUB_ENV"
+          echo "CXX=g++-14" >> "$GITHUB_ENV"
+
+      - name: Python Dependencies
+        id: python_depends
+        run: |
+          export PIP_BREAK_SYSTEM_PACKAGES="1"
+          python3 -m pip install --upgrade pip setuptools
+          pip3 install ./gguf-py
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            -DGGML_RPC=ON
+          time cmake --build build --config Release -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose --timeout 900
+
+      - name: Test llama2c conversion
+        id: llama2c_test
+        run: |
+          cd build
+          echo "Fetch tokenizer"
+          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
+          echo "Fetch llama2c model"
+          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
+          ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
+          ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256

.github/workflows/build-opencl.yml

@@ -0,0 +1,83 @@
+name: CI (opencl)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-opencl.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp',
+      '**/*.cl'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-opencl.yml',
+      'ggml/src/ggml-opencl/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  GGML_NLOOP: 3
+  GGML_N_THREADS: 1
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+
+jobs:
+
+  windows-latest-opencl-adreno:
+    runs-on: windows-2025
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: windows-latest-llvm-arm64-opencl-adreno
+          variant: ccache
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Install Ninja
+        id: install_ninja
+        run: |
+          choco install ninja
+
+      - name: Install OpenCL Headers and Libs
+        id: install_opencl
+        run: |
+          git clone https://github.com/KhronosGroup/OpenCL-Headers
+          cd OpenCL-Headers
+          cmake -B build `
+            -DBUILD_TESTING=OFF `
+            -DOPENCL_HEADERS_BUILD_TESTING=OFF `
+            -DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
+            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
+          cmake --build build --target install
+          git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
+          cd OpenCL-ICD-Loader
+          cmake -B build-arm64-release `
+            -A arm64 `
+            -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
+            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
+          cmake --build build-arm64-release --target install --config release
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -S . -B build -G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON -DLLAMA_BUILD_BORINGSSL=ON
+          cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}

.github/workflows/build-riscv.yml

@@ -34,6 +34,76 @@ env:
   LLAMA_LOG_TIMESTAMPS: 1
 
 jobs:
+  ubuntu-cpu-riscv64-native:
+    runs-on: ubuntu-24.04-riscv
+
+    steps:
+      - name: Install dependencies
+        run: |
+          # Install necessary packages
+          sudo apt-get update
+          sudo apt-get install -y libssl-dev
+
+          # Set gcc-14 and g++-14 as the default compilers
+          sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
+          sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
+
+          git lfs install
+
+      - name: Check environment
+        run: |
+          uname -a
+          gcc --version
+          g++ --version
+          ldd --version
+          cmake --version
+          rustc --version
+
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: ccache
+        uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
+        with:
+          key: ubuntu-cpu-riscv64-native
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DCMAKE_BUILD_TYPE=Release \
+            -DGGML_OPENMP=OFF \
+            -DLLAMA_BUILD_EXAMPLES=ON \
+            -DLLAMA_BUILD_TOOLS=ON \
+            -DLLAMA_BUILD_TESTS=ON \
+            -DCMAKE_C_COMPILER_LAUNCHER=ccache \
+            -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
+            -DGGML_RPC=ON \
+            -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
+            -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
+
+          time cmake --build build --config Release -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose --timeout 900
+
+      - name: Test llama2c conversion
+        id: llama2c_test
+        run: |
+          cd build
+          echo "Fetch tokenizer"
+          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
+          echo "Fetch llama2c model"
+          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
+          ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
+          ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+
   ubuntu-riscv64-native-sanitizer:
     runs-on: ubuntu-24.04-riscv
 

.github/workflows/build-rpc.yml

@@ -0,0 +1,67 @@
+name: CI (rpc)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-rpc.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-rpc.yml',
+      'ggml/src/ggml-rpc/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  GGML_NLOOP: 3
+  GGML_N_THREADS: 1
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+
+jobs:
+
+  ubuntu-latest-rpc:
+    runs-on: ubuntu-latest
+
+    continue-on-error: true
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install build-essential libssl-dev ninja-build
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -G "Ninja" \
+            -DCMAKE_BUILD_TYPE=Release \
+            -DGGML_RPC=ON
+          time cmake --build build --config Release -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose

.github/workflows/build-self-hosted.yml

@@ -67,7 +67,7 @@ jobs:
         id: ggml-ci
         run: |
           nvidia-smi
-          GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+          GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   ggml-ci-nvidia-vulkan-cm:
     runs-on: [self-hosted, Linux, NVIDIA]
@@ -81,7 +81,7 @@ jobs:
         id: ggml-ci
         run: |
           vulkaninfo --summary
-          GG_BUILD_VULKAN=1 GGML_VK_DISABLE_COOPMAT2=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+          GG_BUILD_VULKAN=1 GGML_VK_DISABLE_COOPMAT2=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   ggml-ci-nvidia-vulkan-cm2:
     runs-on: [self-hosted, Linux, NVIDIA, COOPMAT2]
@@ -95,37 +95,36 @@ jobs:
         id: ggml-ci
         run: |
           vulkaninfo --summary
-          GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+          GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
-  # TODO: investigate slight precision issues in some operations for test-backend-ops on the WebGPU backend.
-  #ggml-ci-nvidia-webgpu:
-  #  runs-on: [self-hosted, Linux, NVIDIA]
+  ggml-ci-nvidia-webgpu:
+    runs-on: [self-hosted, Linux, NVIDIA, X64]
 
-  #  steps:
-  #    - name: Clone
-  #      id: checkout
-  #      uses: actions/checkout@v6
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
 
-  #    - name: Dawn Dependency
-  #      id: dawn-depends
-  #      run: |
-  #        DAWN_VERSION="v20260317.182325"
-  #        DAWN_OWNER="google"
-  #        DAWN_REPO="dawn"
-  #        DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
-  #        echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-  #        curl -L -o artifact.tar.gz \
-  #          "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-  #        mkdir dawn
-  #        tar -xvf artifact.tar.gz -C dawn --strip-components=1
+      - name: Dawn Dependency
+        id: dawn-depends
+        run: |
+          DAWN_VERSION="v20260317.182325"
+          DAWN_OWNER="google"
+          DAWN_REPO="dawn"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
+          echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          curl -L -o artifact.tar.gz \
+            "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          mkdir dawn
+          tar -xvf artifact.tar.gz -C dawn --strip-components=1
 
-  #    - name: Test
-  #      id: ggml-ci
-  #      run: |
-  #        GG_BUILD_WEBGPU=1 \
-  #        GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
-  #        GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
-  #          bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+      - name: Test
+        id: ggml-ci
+        run: |
+          GG_BUILD_WEBGPU=1 \
+          GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
+          GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
+            bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   # TODO: provision AMX-compatible machine
   #ggml-ci-cpu-amx:
@@ -139,7 +138,7 @@ jobs:
   #    - name: Test
   #      id: ggml-ci
   #      run: |
-  #        bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+  #        bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   # TODO: provision AMD GPU machine
   # ggml-ci-amd-vulkan:
@@ -154,7 +153,7 @@ jobs:
   #       id: ggml-ci
   #       run: |
   #         vulkaninfo --summary
-  #         GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+  #         GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   # TODO: provision AMD GPU machine
   # ggml-ci-amd-rocm:
@@ -169,7 +168,7 @@ jobs:
   #       id: ggml-ci
   #       run: |
   #         amd-smi static
-  #         GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
+  #         GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   ggml-ci-mac-metal:
     runs-on: [self-hosted, macOS, ARM64]
@@ -296,4 +295,62 @@ jobs:
         id: ggml-ci
         run: |
           source ./openvino_toolkit/setupvars.sh
-          GG_BUILD_OPENVINO=1 GGML_OPENVINO_DEVICE=GPU GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+          GG_BUILD_OPENVINO=1 GGML_OPENVINO_DEVICE=GPU GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+
+  ggml-ci-arm64-cpu-low-perf:
+    runs-on: [self-hosted, Linux, ARM64, CPU]
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Test
+        id: ggml-ci
+        run: |
+          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+
+  ggml-ci-arm64-cpu-high-perf:
+    runs-on: [self-hosted, Linux, ARM64, CPU]
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Test
+        id: ggml-ci
+        run: |
+          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_NO_SVE=1 GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+
+# TODO: not sure how to detect ARM flags on DGX Spark. currently get this error during cmake:
+#         CMake Warning at ggml/src/ggml-cpu/CMakeLists.txt:147 (message):
+#           ARM -march/-mcpu not found, -mcpu=native will be used
+#
+#       if we resolve this, we should be able to offload these jobs to the self-hosted runners
+#
+#  ggml-ci-arm64-cpu-high-perf-sve:
+#    runs-on: [self-hosted, Linux, ARM64, CPU]
+#
+#    steps:
+#      - name: Clone
+#        id: checkout
+#        uses: actions/checkout@v6
+#
+#      - name: Test
+#        id: ggml-ci
+#        run: |
+#          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+#
+#  ggml-ci-arm64-cpu-kleidiai:
+#    runs-on: [self-hosted, Linux, ARM64, CPU]
+#
+#    steps:
+#      - name: Clone
+#        id: checkout
+#        uses: actions/checkout@v6
+#
+#      - name: Test
+#        id: ggml-ci
+#        run: |
+#          GG_BUILD_KLEIDIAI=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp

.github/workflows/build-sycl.yml

@@ -38,18 +38,18 @@ jobs:
   ubuntu-24-sycl:
     strategy:
       matrix:
-        build: [fp32, fp16]
+        build: [fp32]
         include:
           - build: fp32
             fp16: OFF
-          - build: fp16
-            fp16: ON
 
     runs-on: ubuntu-24.04
 
     env:
       ONEAPI_ROOT: /opt/intel/oneapi/
       ONEAPI_INSTALLER_VERSION: "2025.3.3"
+      LEVEL_ZERO_VERSION: "1.28.2"
+      LEVEL_ZERO_UBUNTU_VERSION: "u24.04"
 
     continue-on-error: true
 
@@ -71,6 +71,14 @@ jobs:
           wget https://registrationcenter-download.intel.com/akdlm/IRC_NAS/56f7923a-adb8-43f3-8b02-2b60fcac8cab/intel-deep-learning-essentials-2025.3.3.16_offline.sh -O intel-deep-learning-essentials_offline.sh
           sudo bash intel-deep-learning-essentials_offline.sh -s -a --silent --eula accept
 
+      - name: Install Level Zero SDK
+        shell: bash
+        run: |
+          cd /tmp
+          wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero.deb
+          wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb
+          sudo apt-get install -y ./level-zero.deb ./level-zero-devel.deb
+
       - name: Clone
         id: checkout
         uses: actions/checkout@v6
@@ -107,6 +115,7 @@ jobs:
     env:
       WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/b60765d1-2b85-4e85-86b6-cb0e9563a699/intel-deep-learning-essentials-2025.3.3.18_offline.exe
       WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
+      LEVEL_ZERO_SDK_URL: https://github.com/oneapi-src/level-zero/releases/download/v1.28.2/level-zero-win-sdk-1.28.2.zip
       ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
       ONEAPI_INSTALLER_VERSION: "2025.3.3"
     steps:
@@ -127,6 +136,13 @@ jobs:
         run: |
           scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
 
+      - name: Install Level Zero SDK
+        shell: pwsh
+        run: |
+          Invoke-WebRequest -Uri "${{ env.LEVEL_ZERO_SDK_URL }}" -OutFile "level-zero-win-sdk.zip"
+          Expand-Archive -Path "level-zero-win-sdk.zip" -DestinationPath "C:/level-zero-sdk" -Force
+          "LEVEL_ZERO_V1_SDK_PATH=C:/level-zero-sdk" | Out-File -FilePath $env:GITHUB_ENV -Append
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:

.github/workflows/build-virtgpu.yml

@@ -0,0 +1,50 @@
+name: CI (virtgpu)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-virtgpu.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-virtgpu.yml',
+      'ggml/src/ggml-virtgpu/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  ubuntu-24-virtgpu:
+    runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y build-essential libdrm-dev pkg-config libssl-dev
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DGGML_VIRTGPU=ON \
+            -DGGML_VIRTGPU_BACKEND=ON
+          cmake --build build --config Release -j $(nproc)

.github/workflows/build-webgpu.yml

@@ -0,0 +1,186 @@
+name: CI (webgpu)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-webgpu.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp',
+      '**/*.wgsl'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-webgpu.yml',
+      'ggml/src/ggml-webgpu/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  GGML_NLOOP: 3
+  GGML_N_THREADS: 1
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+
+jobs:
+
+  macOS-latest-arm64-webgpu:
+    runs-on: macos-latest
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: macOS-latest-arm64-webgpu
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Dawn Dependency
+        id: dawn-depends
+        run: |
+          DAWN_VERSION="v20260317.182325"
+          DAWN_OWNER="google"
+          DAWN_REPO="dawn"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
+          echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          curl -L -o artifact.tar.gz \
+            "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          mkdir dawn
+          tar -xvf artifact.tar.gz -C dawn --strip-components=1
+
+      - name: Build
+        id: cmake_build
+        run: |
+          export CMAKE_PREFIX_PATH=dawn
+          cmake -B build -G "Ninja" -DCMAKE_BUILD_TYPE=Release -DGGML_WEBGPU=ON -DGGML_METAL=OFF -DGGML_BLAS=OFF
+          time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose --timeout 900
+
+  ubuntu-24-webgpu:
+    runs-on: ubuntu-24.04
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.21
+        with:
+          key: ubuntu-24-webgpu
+          evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo add-apt-repository -y ppa:kisak/kisak-mesa
+          sudo apt-get update -y
+          sudo apt-get install -y build-essential mesa-vulkan-drivers \
+            libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libssl-dev
+
+      - name: Get latest Vulkan SDK version
+        id: vulkan_sdk_version
+        run: |
+          echo "VULKAN_SDK_VERSION=$(curl https://vulkan.lunarg.com/sdk/latest/linux.txt)" >> "$GITHUB_ENV"
+
+      - name: Use Vulkan SDK Cache
+        uses: actions/cache@v5
+        id: cache-sdk
+        with:
+          path: ./vulkan_sdk
+          key: vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
+
+      - name: Setup Vulkan SDK
+        if: steps.cache-sdk.outputs.cache-hit != 'true'
+        uses: ./.github/actions/linux-setup-vulkan
+        with:
+          path: ./vulkan_sdk
+          version: ${{ env.VULKAN_SDK_VERSION }}
+
+      - name: Dawn Dependency
+        id: dawn-depends
+        run: |
+          sudo apt-get install -y libxrandr-dev libxinerama-dev libxcursor-dev mesa-common-dev libx11-xcb-dev libxi-dev
+          DAWN_VERSION="v20260317.182325"
+          DAWN_OWNER="google"
+          DAWN_REPO="dawn"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
+          echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          curl -L -o artifact.tar.gz \
+            "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
+          mkdir dawn
+          tar -xvf artifact.tar.gz -C dawn --strip-components=1
+
+      - name: Build
+        id: cmake_build
+        run: |
+          export Dawn_DIR=dawn/lib64/cmake/Dawn
+          cmake -B build \
+            -DGGML_WEBGPU=ON
+          time cmake --build build --config Release -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          # This is using llvmpipe and runs slower than other backends
+          # test-backend-ops is too slow on llvmpipe, skip it
+          ctest -L main -E test-backend-ops --verbose --timeout 900
+
+  ubuntu-24-webgpu-wasm:
+    runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Install Emscripten
+        run: |
+          git clone https://github.com/emscripten-core/emsdk.git
+          cd emsdk
+          ./emsdk install latest
+          ./emsdk activate latest
+
+      - name: Fetch emdawnwebgpu
+        run: |
+          DAWN_TAG="v20260317.182325"
+          EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip"
+          echo "Downloading ${EMDAWN_PKG}"
+          curl -L -o emdawn.zip \
+            "https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}"
+          unzip emdawn.zip
+
+      - name: Build WASM WebGPU
+        run: |
+          source emsdk/emsdk_env.sh
+          emcmake cmake -B build-wasm \
+            -G "Ninja" \
+            -DCMAKE_BUILD_TYPE=Release \
+            -DGGML_WEBGPU=ON \
+            -DLLAMA_OPENSSL=OFF \
+            -DEMDAWNWEBGPU_DIR=emdawnwebgpu_pkg
+
+          time cmake --build build-wasm --config Release --target test-backend-ops -j $(nproc)

.github/workflows/build.yml

@@ -132,47 +132,6 @@ jobs:
           cd build
           ctest -L main --verbose --timeout 900
 
-  macOS-latest-arm64-webgpu:
-    runs-on: macos-latest
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: macOS-latest-arm64-webgpu
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Dawn Dependency
-        id: dawn-depends
-        run: |
-          DAWN_VERSION="v20260317.182325"
-          DAWN_OWNER="google"
-          DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
-          echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-          curl -L -o artifact.tar.gz \
-            "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-          mkdir dawn
-          tar -xvf artifact.tar.gz -C dawn --strip-components=1
-
-      - name: Build
-        id: cmake_build
-        run: |
-          export CMAKE_PREFIX_PATH=dawn
-          cmake -B build -G "Ninja" -DCMAKE_BUILD_TYPE=Release -DGGML_WEBGPU=ON -DGGML_METAL=OFF -DGGML_BLAS=OFF
-          time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
-
-      - name: Test
-        id: cmake_test
-        run: |
-          cd build
-          ctest -L main --verbose --timeout 900
-
   ubuntu-cpu:
     strategy:
       matrix:
@@ -181,10 +140,6 @@ jobs:
             os: ubuntu-22.04
           - build: 'arm64'
             os: ubuntu-24.04-arm
-          - build: 's390x'
-            os: ubuntu-24.04-s390x
-          - build: 'ppc64le'
-            os: ubuntu-24.04-ppc64le
 
     runs-on: ${{ matrix.os }}
 
@@ -194,7 +149,6 @@ jobs:
         uses: actions/checkout@v6
 
       - name: ccache
-        if: ${{ matrix.build != 's390x' && matrix.build != 'ppc64le' }}
         uses: ggml-org/ccache-action@v1.2.21
         with:
           key: ubuntu-cpu-${{ matrix.build }}
@@ -224,14 +178,6 @@ jobs:
           python3 -m pip install --upgrade pip setuptools
           pip3 install ./gguf-py
 
-      - name: Swap Endianness
-        id: endianness
-        if: ${{ matrix.build == 's390x' }}
-        run: |
-          for f in models/*.gguf; do
-            echo YES | python3 gguf-py/gguf/scripts/gguf_convert_endian.py $f big
-          done
-
       - name: Build
         id: cmake_build
         run: |
@@ -248,7 +194,6 @@ jobs:
 
       - name: Test llama2c conversion
         id: llama2c_test
-        if: ${{ matrix.build != 's390x' }}
         run: |
           cd build
           echo "Fetch tokenizer"
@@ -258,96 +203,6 @@ jobs:
           ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
           ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
 
-      - name: Test llama2c (s390x)
-        id: llama2c_test_s390x
-        if: ${{ matrix.build == 's390x' }}
-        run: |
-          cd build
-          echo "Fetch llama2c big-endian model"
-          wget https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K-be.gguf
-          ./bin/llama-completion -m stories260K-be.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
-
-  android-arm64:
-    runs-on: ubuntu-latest
-
-    env:
-      NDK_VERSION: "29.0.14206865"
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: android-arm64
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Set up JDK
-        uses: actions/setup-java@v5
-        with:
-          java-version: 17
-          distribution: temurin
-
-      - name: Setup Android SDK
-        uses: android-actions/setup-android@40fd30fb8d7440372e1316f5d1809ec01dcd3699 # v4.0.1
-        with:
-          log-accepted-android-sdk-licenses: false
-
-      - name: Install NDK
-        run: |
-          sdkmanager "ndk;${{ env.NDK_VERSION }}"
-          echo "ANDROID_NDK=${ANDROID_SDK_ROOT}/ndk/${{ env.NDK_VERSION }}" >> $GITHUB_ENV
-
-      - name: Build
-        id: cmake_build
-        run: |
-          cmake -B build \
-            -DCMAKE_TOOLCHAIN_FILE=${ANDROID_NDK}/build/cmake/android.toolchain.cmake \
-            -DANDROID_ABI=arm64-v8a \
-            -DANDROID_PLATFORM=android-28 \
-            -DLLAMA_FATAL_WARNINGS=ON \
-            -DGGML_BACKEND_DL=ON \
-            -DGGML_NATIVE=OFF \
-            -DGGML_CPU_ALL_VARIANTS=ON \
-            -DGGML_OPENMP=OFF \
-            -DLLAMA_BUILD_BORINGSSL=ON \
-            -DGGML_RPC=ON
-          time cmake --build build --config Release -j $(nproc)
-
-  ubuntu-latest-rpc:
-    runs-on: ubuntu-latest
-
-    continue-on-error: true
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Dependencies
-        id: depends
-        run: |
-          sudo apt-get update
-          sudo apt-get install build-essential libssl-dev ninja-build
-
-      - name: Build
-        id: cmake_build
-        run: |
-          cmake -B build \
-            -G "Ninja" \
-            -DCMAKE_BUILD_TYPE=Release \
-            -DGGML_RPC=ON
-          time cmake --build build --config Release -j $(nproc)
-
-      - name: Test
-        id: cmake_test
-        run: |
-          cd build
-          ctest -L main --verbose
-
   ubuntu-24-vulkan:
     strategy:
       matrix:
@@ -387,175 +242,6 @@ jobs:
         run: |
           time cmake --build build -j $(nproc)
 
-  ubuntu-24-webgpu:
-    runs-on: ubuntu-24.04
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ubuntu-24-webgpu
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Dependencies
-        id: depends
-        run: |
-          sudo add-apt-repository -y ppa:kisak/kisak-mesa
-          sudo apt-get update -y
-          sudo apt-get install -y build-essential mesa-vulkan-drivers \
-            libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libssl-dev
-
-      - name: Get latest Vulkan SDK version
-        id: vulkan_sdk_version
-        run: |
-          echo "VULKAN_SDK_VERSION=$(curl https://vulkan.lunarg.com/sdk/latest/linux.txt)" >> "$GITHUB_ENV"
-
-      - name: Use Vulkan SDK Cache
-        uses: actions/cache@v5
-        id: cache-sdk
-        with:
-          path: ./vulkan_sdk
-          key: vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
-
-      - name: Setup Vulkan SDK
-        if: steps.cache-sdk.outputs.cache-hit != 'true'
-        uses: ./.github/actions/linux-setup-vulkan
-        with:
-          path: ./vulkan_sdk
-          version: ${{ env.VULKAN_SDK_VERSION }}
-
-      - name: Dawn Dependency
-        id: dawn-depends
-        run: |
-          sudo apt-get install -y libxrandr-dev libxinerama-dev libxcursor-dev mesa-common-dev libx11-xcb-dev libxi-dev
-          DAWN_VERSION="v20260317.182325"
-          DAWN_OWNER="google"
-          DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
-          echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-          curl -L -o artifact.tar.gz \
-            "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
-          mkdir dawn
-          tar -xvf artifact.tar.gz -C dawn --strip-components=1
-
-      - name: Build
-        id: cmake_build
-        run: |
-          export Dawn_DIR=dawn/lib64/cmake/Dawn
-          cmake -B build \
-            -DGGML_WEBGPU=ON
-          time cmake --build build --config Release -j $(nproc)
-
-      - name: Test
-        id: cmake_test
-        run: |
-          cd build
-          # This is using llvmpipe and runs slower than other backends
-          ctest -L main --verbose --timeout 900
-
-  ubuntu-24-webgpu-wasm:
-    runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Install Emscripten
-        run: |
-          git clone https://github.com/emscripten-core/emsdk.git
-          cd emsdk
-          ./emsdk install latest
-          ./emsdk activate latest
-
-      - name: Fetch emdawnwebgpu
-        run: |
-          DAWN_TAG="v20260317.182325"
-          EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip"
-          echo "Downloading ${EMDAWN_PKG}"
-          curl -L -o emdawn.zip \
-            "https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}"
-          unzip emdawn.zip
-
-      - name: Build WASM WebGPU
-        run: |
-          source emsdk/emsdk_env.sh
-          emcmake cmake -B build-wasm \
-            -G "Ninja" \
-            -DCMAKE_BUILD_TYPE=Release \
-            -DGGML_WEBGPU=ON \
-            -DLLAMA_OPENSSL=OFF \
-            -DEMDAWNWEBGPU_DIR=emdawnwebgpu_pkg
-
-          time cmake --build build-wasm --config Release --target test-backend-ops -j $(nproc)
-
-  ubuntu-22-hip:
-    runs-on: ubuntu-22.04
-    container: rocm/dev-ubuntu-22.04:6.1.2
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Dependencies
-        id: depends
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev rocwmma-dev
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ubuntu-22-hip
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Build with native CMake HIP support
-        id: cmake_build
-        run: |
-          cmake -B build -S . \
-            -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
-            -DGGML_HIP_ROCWMMA_FATTN=ON \
-            -DGPU_TARGETS="gfx1030" \
-            -DGGML_HIP=ON
-          cmake --build build --config Release -j $(nproc)
-
-  ubuntu-22-musa:
-    runs-on: ubuntu-22.04
-    container: mthreads/musa:rc4.3.0-devel-ubuntu22.04-amd64
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Dependencies
-        id: depends
-        run: |
-          apt-get update
-          apt-get install -y build-essential git cmake libssl-dev
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ubuntu-22-musa
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Build with native CMake MUSA support
-        id: cmake_build
-        run: |
-          cmake -B build -S . \
-            -DGGML_MUSA=ON
-          time cmake --build build --config Release -j $(nproc)
-
-
   windows-latest:
     runs-on: windows-2025
 
@@ -579,9 +265,6 @@ jobs:
           - build: 'llvm-arm64'
             arch: 'arm64'
             defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON'
-          - build: 'llvm-arm64-opencl-adreno'
-            arch: 'arm64'
-            defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON'
 
     steps:
       - name: Clone
@@ -623,26 +306,6 @@ jobs:
         run: |
           choco install ninja
 
-      - name: Install OpenCL Headers and Libs
-        id: install_opencl
-        if: ${{ matrix.build == 'llvm-arm64-opencl-adreno' }}
-        run: |
-          git clone https://github.com/KhronosGroup/OpenCL-Headers
-          cd OpenCL-Headers
-          cmake -B build `
-            -DBUILD_TESTING=OFF `
-            -DOPENCL_HEADERS_BUILD_TESTING=OFF `
-            -DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
-            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
-          cmake --build build --target install
-          git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
-          cd OpenCL-ICD-Loader
-          cmake -B build-arm64-release `
-            -A arm64 `
-            -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
-            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
-          cmake --build build-arm64-release --target install --config release
-
       - name: Build
         id: cmake_build
         run: |
@@ -763,145 +426,6 @@ jobs:
           cmake --build build --config Release -j %NINJA_JOBS% -t ggml
           cmake --build build --config Release
 
-
-  windows-latest-hip:
-    runs-on: windows-2022
-
-    env:
-      # Make sure this is in sync with build-cache.yml
-      HIPSDK_INSTALLER_VERSION: "26.Q1"
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Grab rocWMMA package
-        id: grab_rocwmma
-        run: |
-          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70201-81~24.04_amd64.deb"
-          7z x rocwmma.deb
-          7z x data.tar
-
-      - name: Use ROCm Installation Cache
-        uses: actions/cache@v5
-        id: cache-rocm
-        with:
-          path: C:\Program Files\AMD\ROCm
-          key: rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
-
-      - name: Setup ROCm
-        if: steps.cache-rocm.outputs.cache-hit != 'true'
-        uses: ./.github/actions/windows-setup-rocm
-        with:
-          version: ${{ env.HIPSDK_INSTALLER_VERSION }}
-
-      - name: Verify ROCm
-        id: verify
-        run: |
-          # Find and test ROCm installation
-          $clangPath = Get-ChildItem 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | Select-Object -First 1
-          if (-not $clangPath) {
-            Write-Error "ROCm installation not found"
-            exit 1
-          }
-          & $clangPath.FullName --version
-
-      - name: Install ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ${{ github.job }}
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Build
-        id: cmake_build
-        run: |
-          $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
-          $env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
-          cmake -G "Unix Makefiles" -B build -S . `
-            -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
-            -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.1/include/" `
-            -DCMAKE_BUILD_TYPE=Release `
-            -DLLAMA_BUILD_BORINGSSL=ON `
-            -DROCM_DIR="${env:HIP_PATH}" `
-            -DGGML_HIP=ON `
-            -DGGML_HIP_ROCWMMA_FATTN=ON `
-            -DGPU_TARGETS="gfx1100"  `
-            -DGGML_RPC=ON
-          cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
-
-  ubuntu-cpu-riscv64-native:
-    runs-on: ubuntu-24.04-riscv
-
-    steps:
-      - name: Install dependencies
-        run: |
-          # Install necessary packages
-          sudo apt-get update
-          sudo apt-get install -y libssl-dev
-
-          # Set gcc-14 and g++-14 as the default compilers
-          sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
-          sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
-
-          git lfs install
-
-      - name: Check environment
-        run: |
-          uname -a
-          gcc --version
-          g++ --version
-          ldd --version
-          cmake --version
-          rustc --version
-
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
-        with:
-          key: ubuntu-cpu-riscv64-native
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Build
-        id: cmake_build
-        run: |
-          cmake -B build \
-            -DCMAKE_BUILD_TYPE=Release \
-            -DGGML_OPENMP=OFF \
-            -DLLAMA_BUILD_EXAMPLES=ON \
-            -DLLAMA_BUILD_TOOLS=ON \
-            -DLLAMA_BUILD_TESTS=ON \
-            -DCMAKE_C_COMPILER_LAUNCHER=ccache \
-            -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-            -DGGML_RPC=ON \
-            -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-            -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
-
-          time cmake --build build --config Release -j $(nproc)
-
-      - name: Test
-        id: cmake_test
-        run: |
-          cd build
-          ctest -L main --verbose --timeout 900
-
-      - name: Test llama2c conversion
-        id: llama2c_test
-        run: |
-          cd build
-          echo "Fetch tokenizer"
-          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
-          echo "Fetch llama2c model"
-          wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
-          ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
-          ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
-
 # TODO: simplify the following workflows using a matrix
 # TODO: run lighter CI on PRs and the full CI only on master (if needed)
   ggml-ci-x64-cpu-low-perf:
@@ -930,31 +454,32 @@ jobs:
         run: |
           LLAMA_ARG_THREADS=$(nproc) GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
-  ggml-ci-arm64-cpu-low-perf:
-    runs-on: ubuntu-22.04-arm
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ggml-ci-arm64-cpu-low-perf
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Dependencies
-        id: depends
-        run: |
-          sudo apt-get update
-          sudo apt-get install build-essential
-
-      - name: Test
-        id: ggml-ci
-        run: |
-          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+# note: moved to build-self-hosted.yml - can remove from here when everything is stable
+#  ggml-ci-arm64-cpu-low-perf:
+#    runs-on: ubuntu-22.04-arm
+#
+#    steps:
+#      - name: Clone
+#        id: checkout
+#        uses: actions/checkout@v6
+#
+#      - name: ccache
+#        uses: ggml-org/ccache-action@v1.2.21
+#        with:
+#          key: ggml-ci-arm64-cpu-low-perf
+#          evict-old-files: 1d
+#          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+#
+#      - name: Dependencies
+#        id: depends
+#        run: |
+#          sudo apt-get update
+#          sudo apt-get install build-essential
+#
+#      - name: Test
+#        id: ggml-ci
+#        run: |
+#          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
   ggml-ci-x64-cpu-high-perf:
     runs-on: ubuntu-22.04
@@ -982,31 +507,32 @@ jobs:
         run: |
           LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
-  ggml-ci-arm64-cpu-high-perf:
-    runs-on: ubuntu-22.04-arm
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.21
-        with:
-          key: ggml-ci-arm64-cpu-high-perf
-          evict-old-files: 1d
-          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-
-      - name: Dependencies
-        id: depends
-        run: |
-          sudo apt-get update
-          sudo apt-get install build-essential
-
-      - name: Test
-        id: ggml-ci
-        run: |
-          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_NO_SVE=1 GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+# note: moved to build-self-hosted.yml - can remove from here when everything is stable
+#  ggml-ci-arm64-cpu-high-perf:
+#    runs-on: ubuntu-22.04-arm
+#
+#    steps:
+#      - name: Clone
+#        id: checkout
+#        uses: actions/checkout@v6
+#
+#      - name: ccache
+#        uses: ggml-org/ccache-action@v1.2.21
+#        with:
+#          key: ggml-ci-arm64-cpu-high-perf
+#          evict-old-files: 1d
+#          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+#
+#      - name: Dependencies
+#        id: depends
+#        run: |
+#          sudo apt-get update
+#          sudo apt-get install build-essential
+#
+#      - name: Test
+#        id: ggml-ci
+#        run: |
+#          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_NO_SVE=1 GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
   ggml-ci-arm64-cpu-high-perf-sve:
     runs-on: ubuntu-22.04-arm

.github/workflows/check-vendor.yml

@@ -19,7 +19,7 @@ on:
 
 jobs:
   check-vendor:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
 
     steps:
       - name: Checkout

.github/workflows/code-style.yml

@@ -0,0 +1,51 @@
+name: Code Style Checker
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+  pull_request:
+    branches:
+      - master
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  model-naming:
+    runs-on: [self-hosted, fast]
+    steps:
+      - uses: actions/checkout@v6
+      - name: Check model naming conventions
+        run: |
+          python3 - << 'EOF'
+          import re, os, sys
+
+          pairs = re.findall(
+              r'case\s+(LLM_ARCH_\w+)\s*:\s*\n\s+return new (llama_model_\w+)\s*\(',
+              open("src/llama-model.cpp").read())
+
+          errors = []
+          for arch, cls in pairs:
+              suffix  = arch[len("LLM_ARCH_"):]
+              csuffix = cls[len("llama_model_"):]
+              fname   = csuffix.replace("_", "-") + ".cpp"
+
+              if not re.fullmatch(r'[A-Z][A-Z0-9_]*',   suffix):
+                  errors.append(f"{arch}: suffix not upper snake case, example: LLM_ARCH_MY_MODEL")
+
+              if not re.fullmatch(r'[a-z][a-z0-9_]*', csuffix):
+                  errors.append(f"{arch}: class suffix not lower snake case, example: llama_model_my_model")
+
+              elif suffix.lower() != csuffix:
+                  errors.append(f"{arch}: arch/class name mismatch, expected class 'llama_model_{suffix.lower()}' but got '{cls}'")
+
+              elif not os.path.isfile(f"src/models/{fname}"):
+                  errors.append(f"{arch}: expects model file name to be src/models/{fname}, but not found")
+
+          if errors:
+              print('\n'.join(f"  - {e}" for e in errors)); sys.exit(1)
+          print(f"OK: {len(pairs)} mappings validated.")
+          EOF

.github/workflows/docker.yml

@@ -11,6 +11,11 @@ name: Publish Docker image
 
 on:
   workflow_dispatch: # allows manual triggering
+    inputs:
+      skip_s390x:
+        description: "Skip the s390x build target (useful for fast test runs that do not need the IBM Z runner)"
+        type: boolean
+        default: false
   schedule:
     # Rebuild daily rather than on every push because it is expensive
     - cron: '12 4 * * *'
@@ -64,6 +69,8 @@ jobs:
       - name: Generate build and merge matrices
         id: matrices
         shell: bash
+        env:
+          SKIP_S390X: ${{ inputs.skip_s390x || 'false' }}
         run: |
           set -euo pipefail
 
@@ -86,6 +93,11 @@ jobs:
           ]
           JSON
 
+          if [ "${SKIP_S390X}" = "true" ]; then
+            jq 'map(select(.platforms != "linux/s390x"))' build-matrix.json > build-matrix.json.tmp
+            mv build-matrix.json.tmp build-matrix.json
+          fi
+
           BUILD_MATRIX="$(jq -c . build-matrix.json)"
           MERGE_MATRIX="$(jq -c '
             reduce .[] as $entry ({}; .[$entry.tag] |= (
@@ -132,6 +144,7 @@ jobs:
         config: ${{ fromJSON(needs.prepare_matrices.outputs.build_matrix) }}
     steps:
       - name: Check out the repo
+        id: checkout
         uses: actions/checkout@v6
         with:
           fetch-depth: 0
@@ -187,6 +200,10 @@ jobs:
         env:
           GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
 
+      - name: Get build date
+        id: build_date
+        run: echo "date=$(date -u +"%Y-%m-%dT%H:%M:%SZ")" >> $GITHUB_OUTPUT
+
       - name: Free Disk Space (Ubuntu)
         if: ${{ matrix.config.free_disk_space == true }}
         uses: ggml-org/free-disk-space@v1.3.1
@@ -211,13 +228,26 @@ jobs:
         with:
           context: .
           platforms: ${{ matrix.config.platforms }}
-          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
+          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
           file: ${{ matrix.config.dockerfile }}
           target: full
           provenance: false
           build-args: |
+            BUILD_DATE=${{ steps.build_date.outputs.date }}
+            APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
+            APP_REVISION=${{ steps.checkout.outputs.commit }}
+            IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
+            IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
             ${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
             ${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
+          annotations: |
+            manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
+            manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
+            manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
+            manifest:org.opencontainers.image.title=llama.cpp
+            manifest:org.opencontainers.image.description=LLM inference in C/C++
+            manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
+            manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
           # using github experimental cache
           #cache-from: type=gha
           #cache-to: type=gha,mode=max
@@ -235,13 +265,26 @@ jobs:
         with:
           context: .
           platforms: ${{ matrix.config.platforms }}
-          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
+          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
           file: ${{ matrix.config.dockerfile }}
           target: light
           provenance: false
           build-args: |
+            BUILD_DATE=${{ steps.build_date.outputs.date }}
+            APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
+            APP_REVISION=${{ steps.checkout.outputs.commit }}
+            IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
+            IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
             ${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
             ${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
+          annotations: |
+            manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
+            manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
+            manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
+            manifest:org.opencontainers.image.title=llama.cpp
+            manifest:org.opencontainers.image.description=LLM inference in C/C++
+            manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
+            manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
           # using github experimental cache
           #cache-from: type=gha
           #cache-to: type=gha,mode=max
@@ -259,13 +302,26 @@ jobs:
         with:
           context: .
           platforms: ${{ matrix.config.platforms }}
-          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
+          outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
           file: ${{ matrix.config.dockerfile }}
           target: server
           provenance: false
           build-args: |
+            BUILD_DATE=${{ steps.build_date.outputs.date }}
+            APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
+            APP_REVISION=${{ steps.checkout.outputs.commit }}
+            IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
+            IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
             ${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
             ${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
+          annotations: |
+            manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
+            manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
+            manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
+            manifest:org.opencontainers.image.title=llama.cpp
+            manifest:org.opencontainers.image.description=LLM inference in C/C++
+            manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
+            manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
           # using github experimental cache
           #cache-from: type=gha
           #cache-to: type=gha,mode=max
@@ -330,10 +386,15 @@ jobs:
 
     steps:
       - name: Check out the repo
+        id: checkout
         uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
+      - name: Get build date
+        id: build_date
+        run: echo "date=$(date -u +"%Y-%m-%dT%H:%M:%SZ")" >> $GITHUB_OUTPUT
+
       - name: Download digest metadata
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
         with:
@@ -361,6 +422,8 @@ jobs:
           IMAGE_REPO="ghcr.io/${REPO_OWNER}/${REPO_NAME}"
           PREFIX="${IMAGE_REPO}:"
           SRC_TAG="${{ needs.create_tag.outputs.source_tag }}"
+          BUILD_DATE="${{ steps.build_date.outputs.date }}"
+          COMMIT_SHA="${{ steps.checkout.outputs.commit }}"
           TAGS="${{ matrix.config.tag }}"
           ARCHES="${{ matrix.config.arches }}"
           DIGEST_GLOB="/tmp/digests/*.tsv"
@@ -412,11 +475,21 @@ jobs:
                   refs+=("${IMAGE_REPO}@${digest}")
               done
 
+              local annotations=(
+                  --annotation "index:org.opencontainers.image.created=${BUILD_DATE}"
+                  --annotation "index:org.opencontainers.image.version=${SRC_TAG}"
+                  --annotation "index:org.opencontainers.image.revision=${COMMIT_SHA}"
+                  --annotation "index:org.opencontainers.image.title=llama.cpp"
+                  --annotation "index:org.opencontainers.image.description=LLM inference in C/C++"
+                  --annotation "index:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}"
+                  --annotation "index:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}"
+              )
+
               echo "Creating ${merged_tag} from ${refs[*]}"
-              docker buildx imagetools create --tag "${merged_tag}" "${refs[@]}"
+              docker buildx imagetools create "${annotations[@]}" --tag "${merged_tag}" "${refs[@]}"
 
               echo "Creating ${merged_versioned_tag} from ${refs[*]}"
-              docker buildx imagetools create --tag "${merged_versioned_tag}" "${refs[@]}"
+              docker buildx imagetools create "${annotations[@]}" --tag "${merged_versioned_tag}" "${refs[@]}"
           }
 
           for tag in $TAGS; do

.github/workflows/editorconfig.yml

@@ -2,11 +2,6 @@ name: EditorConfig Checker
 
 on:
   workflow_dispatch: # allows manual triggering
-    inputs:
-      create_release:
-        description: 'Create new release'
-        required: true
-        type: boolean
   push:
     branches:
       - master
@@ -20,7 +15,7 @@ concurrency:
 
 jobs:
   editorconfig:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
     steps:
       - uses: actions/checkout@v6
       - uses: editorconfig-checker/action-editorconfig-checker@840e866d93b8e032123c23bac69dece044d4d84c # v2.2.0

.github/workflows/gguf-publish.yml

@@ -29,10 +29,10 @@ jobs:
       uses: actions/setup-python@v6
       with:
         python-version: '3.11'
+        pip-install: poetry==2.4.0
     - name: Install dependencies
       run: |
         cd gguf-py
-        python -m pip install poetry==2.3.2
         poetry install
 
     - name: Build package

.github/workflows/pre-tokenizer-hashes.yml

@@ -3,16 +3,16 @@ name: Check Pre-Tokenizer Hashes
 on:
     push:
         paths:
-            - 'convert_hf_to_gguf.py'
+            - 'conversion/base.py'
             - 'convert_hf_to_gguf_update.py'
     pull_request:
         paths:
-            - 'convert_hf_to_gguf.py'
+            - 'conversion/base.py'
             - 'convert_hf_to_gguf_update.py'
 
 jobs:
     pre-tokenizer-hashes:
-        runs-on: ubuntu-slim
+        runs-on: [self-hosted, fast]
 
         steps:
         - name: Checkout repository
@@ -30,16 +30,16 @@ jobs:
 
         - name: Update pre-tokenizer hashes
           run: |
-              cp convert_hf_to_gguf.py /tmp
+              cp conversion/base.py /tmp
               .venv/bin/python convert_hf_to_gguf_update.py --check-missing
 
         - name: Check if committed pre-tokenizer hashes matches generated version
           run: |
-              if ! diff -q convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py; then
-                  echo "Model pre-tokenizer hashes (in convert_hf_to_gguf.py) do not match generated hashes (from convert_hf_to_gguf_update.py)."
-                  echo "To fix: run ./convert_hf_to_gguf_update.py and commit the updated convert_hf_to_gguf.py along with your changes"
+              if ! diff -q conversion/base.py /tmp/base.py; then
+                  echo "Model pre-tokenizer hashes (in conversion/base.py) do not match generated hashes (from convert_hf_to_gguf_update.py)."
+                  echo "To fix: run ./convert_hf_to_gguf_update.py and commit the updated conversion/base.py along with your changes"
                   echo "Differences found:"
-                  diff convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py || true
+                  diff conversion/base.py /tmp/base.py || true
                   exit 1
               fi
               echo "Model pre-tokenizer hashes are up to date."

.github/workflows/python-check-requirements.yml

@@ -20,7 +20,7 @@ concurrency:
 
 jobs:
   python-check-requirements:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, CPU, fast]
     name: check-requirements
     steps:
       - name: Check out source repository

.github/workflows/python-lint.yml

@@ -21,7 +21,7 @@ concurrency:
 
 jobs:
   flake8-lint:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
     name: Lint
     steps:
       - name: Check out source repository

.github/workflows/python-type-check.yml

@@ -22,7 +22,7 @@ concurrency:
 
 jobs:
   python-type-check:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
     name: python type-check
     steps:
       - name: Check out source repository
@@ -31,7 +31,7 @@ jobs:
         uses: actions/setup-python@v6
         with:
           python-version: "3.11"
-          pip-install: -r requirements/requirements-all.txt ty==0.0.26
+          pip-install: -r requirements/requirements-all.txt ty==0.0.35
       # - name: Type-check with Pyright
       #   uses: jakebailey/pyright-action@v2
       #   with:

.github/workflows/release.yml

@@ -36,7 +36,9 @@ env:
   CMAKE_ARGS: "-DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON"
 
 jobs:
+
   macOS-cpu:
+
     strategy:
       matrix:
         include:
@@ -64,6 +66,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -91,7 +100,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-${{ matrix.build }}.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-${{ matrix.build }}.tar.gz -s ",^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -100,6 +109,7 @@ jobs:
           name: llama-bin-macos-${{ matrix.build }}.tar.gz
 
   ubuntu-cpu:
+
     strategy:
       matrix:
         include:
@@ -119,6 +129,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         if: ${{ matrix.build != 's390x' }}
         uses: ggml-org/ccache-action@v1.2.21
@@ -160,7 +177,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -169,6 +186,7 @@ jobs:
           name: llama-bin-ubuntu-${{ matrix.build }}.tar.gz
 
   ubuntu-vulkan:
+
     strategy:
       matrix:
         include:
@@ -186,6 +204,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -228,7 +253,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -237,6 +262,7 @@ jobs:
           name: llama-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz
 
   android-arm64:
+
     runs-on: ubuntu-latest
 
     env:
@@ -249,6 +275,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -297,7 +330,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-android-arm64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-android-arm64.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -306,6 +339,7 @@ jobs:
           name: llama-bin-android-arm64.tar.gz
 
   ubuntu-24-openvino:
+
     runs-on: ubuntu-24.04
 
     outputs:
@@ -327,6 +361,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -377,7 +418,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/ReleaseOV/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-openvino-${{ env.OPENVINO_VERSION_MAJOR }}-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/ReleaseOV/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-openvino-${{ env.OPENVINO_VERSION_MAJOR }}-x64.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/ReleaseOV/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -386,6 +427,7 @@ jobs:
           name: llama-bin-ubuntu-openvino-${{ env.OPENVINO_VERSION_MAJOR }}-x64.tar.gz
 
   windows-cpu:
+
     runs-on: windows-2025
 
     strategy:
@@ -400,6 +442,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -438,6 +487,7 @@ jobs:
           name: llama-bin-win-cpu-${{ matrix.arch }}.zip
 
   windows:
+
     runs-on: windows-2025
 
     env:
@@ -461,6 +511,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -520,6 +577,7 @@ jobs:
           name: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
 
   windows-cuda:
+
     runs-on: windows-2022
 
     strategy:
@@ -531,6 +589,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Install ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -591,6 +656,7 @@ jobs:
           name: cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
 
   windows-sycl:
+
     runs-on: windows-2022
 
     defaults:
@@ -600,6 +666,7 @@ jobs:
     env:
       WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/b60765d1-2b85-4e85-86b6-cb0e9563a699/intel-deep-learning-essentials-2025.3.3.18_offline.exe
       WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
+      LEVEL_ZERO_SDK_URL: https://github.com/oneapi-src/level-zero/releases/download/v1.28.2/level-zero-win-sdk-1.28.2.zip
       ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
       ONEAPI_INSTALLER_VERSION: "2025.3.3"
 
@@ -621,6 +688,20 @@ jobs:
         run: |
           scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
 
+      - name: Install Level Zero SDK
+        shell: pwsh
+        run: |
+          Invoke-WebRequest -Uri "${{ env.LEVEL_ZERO_SDK_URL }}" -OutFile "level-zero-win-sdk.zip"
+          Expand-Archive -Path "level-zero-win-sdk.zip" -DestinationPath "C:/level-zero-sdk" -Force
+          "LEVEL_ZERO_V1_SDK_PATH=C:/level-zero-sdk" | Out-File -FilePath $env:GITHUB_ENV -Append
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -655,6 +736,13 @@ jobs:
           cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_opencl.dll" ./build/bin
           cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_loader.dll" ./build/bin
           cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_win_proxy_loader.dll" ./build/bin
+          ZE_LOADER_DLL=$(find "${{ env.ONEAPI_ROOT }}" "$LEVEL_ZERO_V1_SDK_PATH" -iname ze_loader.dll -print -quit 2>/dev/null || true)
+          if [ -n "$ZE_LOADER_DLL" ]; then
+            echo "Using Level Zero loader: $ZE_LOADER_DLL"
+            cp "$ZE_LOADER_DLL" ./build/bin
+          else
+            echo "Level Zero loader DLL not found in oneAPI or SDK; relying on system driver/runtime"
+          fi
 
           cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl8.dll" ./build/bin
           cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin
@@ -681,20 +769,21 @@ jobs:
           name: llama-bin-win-sycl-x64.zip
 
   ubuntu-24-sycl:
+
     strategy:
       matrix:
-        build: [fp32, fp16]
+        build: [fp32]
         include:
           - build: fp32
             fp16: OFF
-          - build: fp16
-            fp16: ON
 
     runs-on: ubuntu-24.04
 
     env:
       ONEAPI_ROOT: /opt/intel/oneapi/
       ONEAPI_INSTALLER_VERSION: "2025.3.3"
+      LEVEL_ZERO_VERSION: "1.28.2"
+      LEVEL_ZERO_UBUNTU_VERSION: "u24.04"
 
     steps:
       - name: Clone
@@ -718,6 +807,21 @@ jobs:
           wget https://registrationcenter-download.intel.com/akdlm/IRC_NAS/56f7923a-adb8-43f3-8b02-2b60fcac8cab/intel-deep-learning-essentials-2025.3.3.16_offline.sh -O intel-deep-learning-essentials_offline.sh
           sudo bash intel-deep-learning-essentials_offline.sh -s -a --silent --eula accept
 
+      - name: Install Level Zero SDK
+        shell: bash
+        run: |
+          cd /tmp
+          wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero.deb
+          wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb
+          sudo apt-get install -y ./level-zero.deb ./level-zero-devel.deb
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
         uses: ggml-org/ccache-action@v1.2.21
         with:
@@ -748,7 +852,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-${{ matrix.build }}-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-${{ matrix.build }}-x64.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -757,6 +861,7 @@ jobs:
           name: llama-bin-ubuntu-sycl-${{ matrix.build }}-x64.tar.gz
 
   ubuntu-22-rocm:
+
     runs-on: ubuntu-22.04
 
     strategy:
@@ -773,6 +878,13 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Free up disk space
         uses: ggml-org/free-disk-space@v1.3.1
         with:
@@ -851,7 +963,7 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -860,6 +972,7 @@ jobs:
           name: llama-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz
 
   windows-hip:
+
     runs-on: windows-2022
 
     env:
@@ -876,6 +989,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Grab rocWMMA package
         id: grab_rocwmma
         run: |
@@ -986,6 +1106,7 @@ jobs:
             -DGGML_METAL_USE_BF16=ON \
             -DGGML_METAL_EMBED_LIBRARY=ON \
             -DLLAMA_OPENSSL=OFF \
+            -DLLAMA_BUILD_APP=OFF \
             -DLLAMA_BUILD_EXAMPLES=OFF \
             -DLLAMA_BUILD_TOOLS=OFF \
             -DLLAMA_BUILD_TESTS=OFF \
@@ -1103,7 +1224,7 @@ jobs:
       - name: Pack artifacts
         run: |
           cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -1111,6 +1232,9 @@ jobs:
           path: llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz
           name: llama-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz
 
+  ui-build:
+    uses: ./.github/workflows/ui-build.yml
+
   release:
     if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
 
@@ -1136,6 +1260,10 @@ jobs:
       - macOS-cpu
       - ios-xcode-build
       - openEuler-cann
+      - ui-build
+
+    outputs:
+      tag_name: ${{ steps.tag.outputs.name }}
 
     steps:
       - name: Clone
@@ -1192,6 +1320,18 @@ jobs:
           mv -v artifact/*.zip release
           mv -v artifact/*.tar.gz release
 
+      - name: Download UI build
+        id: download_ui
+        uses: actions/download-artifact@v7
+        with:
+          name: ui-build
+          path: ./ui-dist
+
+      - name: Package UI
+        id: package_ui
+        run: |
+          tar -czvf release/llama-${{ steps.tag.outputs.name }}-ui.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./ui-dist .
+
       - name: Create release
         id: create_release
         uses: ggml-org/action-create-release@v1
@@ -1221,7 +1361,6 @@ jobs:
             - [Ubuntu x64 (ROCm 7.2)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-7.2-x64.tar.gz)
             - [Ubuntu x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-openvino-${{ needs.ubuntu-24-openvino.outputs.openvino_version }}-x64.tar.gz)
             - [Ubuntu x64 (SYCL FP32)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-fp32-x64.tar.gz)
-            - [Ubuntu x64 (SYCL FP16)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-fp16-x64.tar.gz)
 
             **Android:**
             - [Android arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-android-arm64.tar.gz)
@@ -1241,6 +1380,9 @@ jobs:
             - [openEuler aarch64 (310p)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-310p-openEuler-aarch64.tar.gz)
             - [openEuler aarch64 (910b, ACL Graph)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-910b-openEuler-aarch64-aclgraph.tar.gz)
 
+            **UI:**
+            - [UI](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-ui.tar.gz)
+
       - name: Upload release
         id: upload_release
         uses: actions/github-script@v8
@@ -1262,3 +1404,15 @@ jobs:
                 });
               }
             }
+
+  ui-publish:
+    if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
+
+    needs:
+      - release
+
+    uses: ./.github/workflows/ui-publish.yml
+    with:
+      version_tag: ${{ needs.release.outputs.tag_name }}
+    secrets:
+      hf_token: ${{ secrets.HF_TOKEN_UI_STATIC_OUTPUT }}

.github/workflows/server-sanitize.yml

@@ -67,6 +67,13 @@ jobs:
           fetch-depth: 0
           ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Build
         id: cmake_build
         run: |

.github/workflows/server-self-hosted.yml

@@ -67,6 +67,13 @@ jobs:
           fetch-depth: 0
           ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Build
         id: cmake_build
         run: |
@@ -84,42 +91,106 @@ jobs:
           export ${{ matrix.extra_args }}
           pytest -v -x -m "not slow"
 
-  # TODO: provision CUDA runner
-  #  server-cuda:
-  #    runs-on: [self-hosted, llama-server, Linux, NVIDIA]
-  #
-  #    name: server-cuda (${{ matrix.wf_name }})
-  #    strategy:
-  #      matrix:
-  #        build_type: [Release]
-  #        wf_name: ["GPUx1"]
-  #        include:
-  #          - build_type: Release
-  #            extra_args: "LLAMA_ARG_BACKEND_SAMPLING=1"
-  #            wf_name:    "GPUx1, backend-sampling"
-  #      fail-fast: false
-  #
-  #    steps:
-  #      - name: Clone
-  #        id: checkout
-  #        uses: actions/checkout@v6
-  #        with:
-  #          fetch-depth: 0
-  #          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
-  #
-  #      - name: Build
-  #        id: cmake_build
-  #        run: |
-  #          cmake -B build -DGGML_SCHED_NO_REALLOC=ON
-  #          cmake --build build --config ${{ matrix.build_type }} -j $(sysctl -n hw.logicalcpu) --target llama-server
-  #
-  #      - name: Tests
-  #        id: server_integration_tests
-  #        if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
-  #        run: |
-  #          cd tools/server/tests
-  #          python3 -m venv venv
-  #          source venv/bin/activate
-  #          pip install -r requirements.txt
-  #          export ${{ matrix.extra_args }}
-  #          pytest -v -x -m "not slow"
+  server-cuda:
+    runs-on: [self-hosted, llama-server, Linux, NVIDIA]
+
+    name: server-cuda (${{ matrix.wf_name }})
+    strategy:
+      matrix:
+        build_type: [Release]
+        wf_name: ["GPUx1"]
+        include:
+          - build_type: Release
+            extra_args: "LLAMA_ARG_BACKEND_SAMPLING=1"
+            wf_name:    "GPUx1, backend-sampling"
+      fail-fast: false
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build -DGGML_CUDA=ON -DGGML_SCHED_NO_REALLOC=ON
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
+
+      - name: Tests
+        id: server_integration_tests
+        if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
+        run: |
+          cd tools/server/tests
+          python3 -m venv venv
+          source venv/bin/activate
+          pip install -r requirements.txt
+          export ${{ matrix.extra_args }}
+          pytest -v -x -m "not slow"
+
+  server-kleidiai:
+    runs-on: ah-ubuntu_22_04-c8g_8x
+
+    name: server-kleidiai (${{ matrix.wf_name }})
+    strategy:
+      matrix:
+        include:
+          - build_type: Release
+            extra_build_flags: "-DGGML_CPU_KLEIDIAI=ON"
+            extra_args: ""
+            wf_name:    "CPUx1, kleidiai"
+      fail-fast: false
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Dependencies
+        id: depends
+        run: |
+          set -euxo pipefail
+          sudo apt-get update
+          sudo DEBIAN_FRONTEND=noninteractive NEEDRESTART_MODE=a \
+          apt-get install -y \
+           build-essential \
+           libssl-dev \
+           python3-venv \
+           gpg \
+           wget \
+           time \
+           git-lfs
+
+          git lfs install
+
+          # install the latest cmake
+          sudo install -d /usr/share/keyrings
+          wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc \
+           | gpg --dearmor \
+           | sudo tee /usr/share/keyrings/kitware-archive-keyring.gpg >/dev/null
+          echo 'deb [signed-by=/usr/share/keyrings/kitware-archive-keyring.gpg] https://apt.kitware.com/ubuntu/ jammy main' \
+           | sudo tee /etc/apt/sources.list.d/kitware.list
+          sudo apt-get update
+          sudo apt-get install -y cmake
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build -DGGML_SCHED_NO_REALLOC=ON ${{ matrix.extra_build_flags }}
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
+
+      - name: Tests
+        id: server_integration_tests
+        if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
+        run: |
+          cd tools/server/tests
+          python3 -m venv venv
+          source venv/bin/activate
+          pip install -r requirements.txt
+          export ${{ matrix.extra_args }}
+          pytest -v -x -m "not slow"

.github/workflows/server.yml

@@ -54,8 +54,13 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
+  ui-build:
+    name: Build Web UI
+    uses: ./.github/workflows/ui-build.yml
+
   server:
     runs-on: ubuntu-latest
+    needs: ui-build
 
     name: server (${{ matrix.wf_name }})
     strategy:
@@ -93,6 +98,12 @@ jobs:
           fetch-depth: 0
           ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
 
+      - name: Download built UI
+        uses: actions/download-artifact@v7
+        with:
+          name: ui-build
+          path: tools/ui/dist
+
       - name: Build
         id: cmake_build
         run: |
@@ -135,6 +146,11 @@ jobs:
           fetch-depth: 0
           ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+
       - name: Build
         id: cmake_build
         run: |

.github/workflows/ui-build.yml

@@ -0,0 +1,43 @@
+name: UI Build
+
+on:
+  workflow_call:
+
+jobs:
+  build:
+    runs-on: [self-hosted, fast]
+    env:
+      BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
+      - name: Install dependencies
+        run: npm ci
+        working-directory: tools/ui
+
+      - name: Build application
+        run: npm run build
+        working-directory: tools/ui
+
+      - name: Generate checksums
+        run: |
+          cd tools/ui/dist
+          for f in *; do
+            sha256sum "$f" | awk '{print $1, $2}' >> checksums.txt
+          done
+
+      - name: Upload built UI
+        uses: actions/upload-artifact@v6
+        with:
+          name: ui-build
+          path: tools/ui/dist/
+          retention-days: 1

.github/workflows/ui-publish.yml

@@ -0,0 +1,70 @@
+name: UI Publish
+
+on:
+  workflow_call:
+    inputs:
+      version_tag:
+        description: 'Version tag to publish under (e.g., b1234)'
+        required: true
+        type: string
+    secrets:
+      hf_token:
+        description: 'Hugging Face token with write access'
+        required: true
+
+jobs:
+  build:
+    name: Build static output
+    uses: ./.github/workflows/ui-build.yml
+
+  publish:
+    name: Publish UI Static Output
+    needs: build
+    runs-on: ubuntu-24.04-arm
+
+    permissions:
+      contents: read
+
+    env:
+      HF_BUCKET_NAME: ${{ vars.HF_BUCKET_UI_STATIC_OUTPUT }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 1
+
+      - name: Download UI build artifact
+        uses: actions/download-artifact@v7
+        with:
+          name: ui-build
+          path: tools/ui/dist/
+
+      - name: Install Hugging Face Hub CLI
+        run: pip install -U huggingface_hub
+
+      - name: Authenticate with Hugging Face
+        run: hf auth login --token ${{ secrets.hf_token }}
+
+      - name: Sync built files to Hugging Face bucket (version tag)
+        run: |
+          # Upload the built files to the Hugging Face bucket under the release version
+          hf buckets sync tools/ui/dist hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/${{ inputs.version_tag }} --delete --quiet
+
+      - name: Sync built files to Hugging Face bucket (latest)
+        run: |
+          # Also upload to the 'latest' directory for fallback downloads
+          hf buckets sync tools/ui/dist hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/latest --delete --quiet
+
+      - name: Verify upload
+        run: |
+          # List the files in the bucket to verify the upload
+          hf buckets list hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/${{ inputs.version_tag }} -R -h
+
+      - name: Clean up root-level files
+        run: |
+          # Clean up any old root-level files from previous non-versioned deployments
+          hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/index.html --yes 2>/dev/null || true
+          hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/bundle.js --yes 2>/dev/null || true
+          hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/bundle.css --yes 2>/dev/null || true
+          hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/loading.html --yes 2>/dev/null || true

.github/workflows/ui-self-hosted.yml

@@ -0,0 +1,118 @@
+name: UI (self-hosted)
+
+# these are the same as ui.yml, but with self-hosted runners
+# the runners come with pre-installed Playwright browsers version: 1.56.1
+# the jobs are much lighter because they don't need to install node and playwright browsers
+
+on:
+  workflow_dispatch:
+    inputs:
+      sha:
+        description: 'Commit SHA1 to build'
+        required: false
+        type: string
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/ui-self-hosted.yml',
+      '.github/workflows/ui-build.yml',
+      'tools/ui/**.*',
+      'tools/server/tests/**.*'
+    ]
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/ui-self-hosted.yml',
+      '.github/workflows/ui-build.yml',
+      'tools/ui/**.*',
+      'tools/server/tests/**.*'
+    ]
+
+env:
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+  LLAMA_LOG_VERBOSITY: 10
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  ui-build:
+    name: Build static output
+    uses: ./.github/workflows/ui-build.yml
+
+  ui-checks:
+    name: Checks
+    needs: ui-build
+    runs-on: [self-hosted, PLAYWRIGHT]
+    continue-on-error: true
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Install dependencies
+        id: setup
+        run: npm ci
+        working-directory: tools/ui
+
+      - name: Run type checking
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run check
+        working-directory: tools/ui
+
+      - name: Run linting
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run lint
+        working-directory: tools/ui
+
+      - name: Run Client tests
+        if: ${{ always() }}
+        run: npm run test:client
+        working-directory: tools/ui
+
+      - name: Run Unit tests
+        if: ${{ always() }}
+        run: npm run test:unit
+        working-directory: tools/ui
+
+  e2e-tests:
+    name: E2E Tests
+    needs: ui-build
+    runs-on: [self-hosted, PLAYWRIGHT]
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Install dependencies
+        id: setup
+        run: npm ci
+        working-directory: tools/ui
+
+      - name: Build application
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run build
+        working-directory: tools/ui
+
+      - name: Build Storybook
+        if: ${{ always() }}
+        run: npm run build-storybook
+        working-directory: tools/ui
+
+      - name: Run UI tests
+        if: ${{ always() }}
+        run: npm run test:ui -- --testTimeout=60000
+        working-directory: tools/ui
+
+      - name: Run E2E tests
+        if: ${{ always() }}
+        run: npm run test:e2e
+        working-directory: tools/ui

.github/workflows/ui.yml

@@ -1,7 +1,7 @@
-name: Server WebUI
+name: UI
 
 on:
-  workflow_dispatch: # allows manual triggering
+  workflow_dispatch:
     inputs:
       sha:
         description: 'Commit SHA1 to build'
@@ -11,18 +11,18 @@ on:
     branches:
       - master
     paths: [
-      '.github/workflows/server-webui.yml',
-      'tools/server/webui/**.*',
-      'tools/server/tests/**.*',
-      'tools/server/public/**'
+      '.github/workflows/ui.yml',
+      '.github/workflows/ui-build.yml',
+      'tools/ui/**.*',
+      'tools/server/tests/**.*'
     ]
   pull_request:
     types: [opened, synchronize, reopened]
     paths: [
-      '.github/workflows/server-webui.yml',
-      'tools/server/webui/**.*',
-      'tools/server/tests/**.*',
-      'tools/server/public/**'
+      '.github/workflows/ui.yml',
+      '.github/workflows/ui-build.yml',
+      'tools/ui/**.*',
+      'tools/server/tests/**.*'
     ]
 
 env:
@@ -36,9 +36,14 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  webui-check:
-    name: WebUI Checks
-    runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
+  ui-build:
+    name: Build static output
+    uses: ./.github/workflows/ui-build.yml
+
+  ui-checks:
+    name: Checks
+    needs: ui-build
+    runs-on: ubuntu-latest
     continue-on-error: true
     steps:
       - name: Checkout code
@@ -51,58 +56,89 @@ jobs:
         id: node
         uses: actions/setup-node@v6
         with:
-          node-version: "22"
+          node-version: "24"
           cache: "npm"
-          cache-dependency-path: "tools/server/webui/package-lock.json"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Install dependencies
         id: setup
         if: ${{ steps.node.conclusion == 'success' }}
         run: npm ci
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Run type checking
         if: ${{ always() && steps.setup.conclusion == 'success' }}
         run: npm run check
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Run linting
         if: ${{ always() && steps.setup.conclusion == 'success' }}
         run: npm run lint
-        working-directory: tools/server/webui
-
-      - name: Build application
-        if: ${{ always() && steps.setup.conclusion == 'success' }}
-        run: npm run build
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Install Playwright browsers
         id: playwright
         if: ${{ always() && steps.setup.conclusion == 'success' }}
         run: npx playwright install --with-deps
-        working-directory: tools/server/webui
-
-      - name: Build Storybook
-        if: ${{ always() && steps.playwright.conclusion == 'success' }}
-        run: npm run build-storybook
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Run Client tests
         if: ${{ always() && steps.playwright.conclusion == 'success' }}
         run: npm run test:client
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Run Unit tests
         if: ${{ always() && steps.playwright.conclusion == 'success' }}
         run: npm run test:unit
-        working-directory: tools/server/webui
+        working-directory: tools/ui
+
+  e2e-tests:
+    name: E2E Tests
+    needs: ui-build
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Setup Node.js
+        id: node
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
+      - name: Install dependencies
+        id: setup
+        if: ${{ steps.node.conclusion == 'success' }}
+        run: npm ci
+        working-directory: tools/ui
+
+      - name: Build application
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run build
+        working-directory: tools/ui
+
+      - name: Install Playwright browsers
+        id: playwright
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npx playwright install --with-deps
+        working-directory: tools/ui
+
+      - name: Build Storybook
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run build-storybook
+        working-directory: tools/ui
 
       - name: Run UI tests
         if: ${{ always() && steps.playwright.conclusion == 'success' }}
         run: npm run test:ui -- --testTimeout=60000
-        working-directory: tools/server/webui
+        working-directory: tools/ui
 
       - name: Run E2E tests
         if: ${{ always() && steps.playwright.conclusion == 'success' }}
         run: npm run test:e2e
-        working-directory: tools/server/webui
+        working-directory: tools/ui

.github/workflows/update-ops-docs.yml

@@ -3,18 +3,20 @@ name: Update Operations Documentation
 on:
     push:
         paths:
+            - '.github/workflows/update-ops-docs.yml'
             - 'docs/ops.md'
             - 'docs/ops/**'
             - 'scripts/create_ops_docs.py'
     pull_request:
         paths:
+            - '.github/workflows/update-ops-docs.yml'
             - 'docs/ops.md'
             - 'docs/ops/**'
             - 'scripts/create_ops_docs.py'
 
 jobs:
     update-ops-docs:
-        runs-on: ubuntu-slim
+        runs-on: [self-hosted, fast, ARM64]
 
         steps:
         - name: Checkout repository

.gitignore

@@ -92,12 +92,12 @@
 !/examples/sycl/*.bat
 !/examples/sycl/*.sh
 
-# Server Web UI temporary files
+# Server Web UI temporary files (+ legacy directory)
 
 /tools/server/webui/node_modules
 /tools/server/webui/dist
-# we no longer use gz for index.html
-/tools/server/public/index.html.gz
+/tools/ui/node_modules
+/tools/ui/dist
 
 # Python
 
@@ -105,9 +105,12 @@
 __pycache__/
 */poetry.lock
 poetry.toml
+poetry.lock
+uv.lock
 
 # Nix
 
+flake.lock
 /result
 
 # Test binaries

.pi/gg/SYSTEM.md

@@ -1,9 +1,10 @@
 You are a coding agent. Here are some very important rules that you must follow:
 
 General:
-- By very precise and concise when writing code, comments, explanations, etc.
+- Be very precise and concise when writing code, comments, explanations, etc.
 - PR and commit titles format: `<module> : <title>`. Lookup recents for examples
 - Don't try to build or run the code unless you are explicitly asked to do so
+- Use the `gh` CLI tool when querying PRs, issues, or other GitHub resources
 
 Coding:
 - When in doubt, always refer to the CONTRIBUTING.md file of the project
@@ -15,12 +16,15 @@ Pull requests (PRs):
 - New branch names are prefixed with "gg/"
 - Before opening a pull request, ask the user to confirm the description
 - When creating a pull request, look for the repository's PR template and follow it
-- For the AI usage disclosure section, write "YES. llama.cpp + pi"
+- For the AI usage disclosure section, write "YES. llama.cpp + pi + [MODEL]"
+- Ask the user to tell you what model was used and write it in place of [MODEL]
 - Always create the pull requests in draft mode
 
 Commits:
 - On every commit that you make, include a "Assisted-by: llama.cpp:local pi" tag
 - Do not explicitly set the git author in commits - rely on the default git config
+- Always use `--no-gpg-sign` when committing
+- Never `git push` without explicit confirmation from the user
 
 Resources (read on demand):
 - [CONTRIBUTING.md](CONTRIBUTING.md)

CMakeLists.txt

@@ -104,13 +104,16 @@ option(LLAMA_SANITIZE_UNDEFINED "llama: enable undefined sanitizer" OFF)
 option(LLAMA_BUILD_COMMON "llama: build common utils library" ${LLAMA_STANDALONE})
 
 # extra artifacts
-option(LLAMA_BUILD_TESTS    "llama: build tests"          ${LLAMA_STANDALONE})
-option(LLAMA_BUILD_TOOLS    "llama: build tools"          ${LLAMA_STANDALONE})
-option(LLAMA_BUILD_EXAMPLES "llama: build examples"       ${LLAMA_STANDALONE})
-option(LLAMA_BUILD_SERVER   "llama: build server example" ${LLAMA_STANDALONE})
-option(LLAMA_BUILD_WEBUI    "llama: build the embedded Web UI for server"  ON)
-option(LLAMA_TOOLS_INSTALL  "llama: install tools"        ${LLAMA_TOOLS_INSTALL_DEFAULT})
-option(LLAMA_TESTS_INSTALL  "llama: install tests"        ON)
+option(LLAMA_BUILD_TESTS     "llama: build tests"                                                                ${LLAMA_STANDALONE})
+option(LLAMA_BUILD_TOOLS     "llama: build tools"                                                                ${LLAMA_STANDALONE})
+option(LLAMA_BUILD_EXAMPLES  "llama: build examples"                                                             ${LLAMA_STANDALONE})
+option(LLAMA_BUILD_SERVER    "llama: build server example"                                                       ${LLAMA_STANDALONE})
+option(LLAMA_BUILD_APP       "llama: build the unified binary"                                                   ${LLAMA_STANDALONE})
+option(LLAMA_BUILD_UI        "llama: build the embedded Web UI for server"                                       ON)
+option(LLAMA_USE_PREBUILT_UI "llama: use prebuilt UI from HF Bucket when available (requires LLAMA_BUILD_UI=ON)" ON)
+
+option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT})
+option(LLAMA_TESTS_INSTALL "llama: install tests" ON)
 
 # 3rd party libs
 option(LLAMA_OPENSSL    "llama: use openssl to support HTTPS" ON)
@@ -215,6 +218,10 @@ if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TOOLS)
     add_subdirectory(tools)
 endif()
 
+if (LLAMA_BUILD_APP)
+    add_subdirectory(app)
+endif()
+
 # Automatically add all files from the 'licenses' directory
 file(GLOB EXTRA_LICENSES "${CMAKE_SOURCE_DIR}/licenses/LICENSE-*")
 
@@ -270,18 +277,6 @@ install(FILES ${CMAKE_CURRENT_BINARY_DIR}/llama-config.cmake
               ${CMAKE_CURRENT_BINARY_DIR}/llama-version.cmake
         DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/llama)
 
-install(
-    FILES convert_hf_to_gguf.py
-    PERMISSIONS
-        OWNER_READ
-        OWNER_WRITE
-        OWNER_EXECUTE
-        GROUP_READ
-        GROUP_EXECUTE
-        WORLD_READ
-        WORLD_EXECUTE
-    DESTINATION ${CMAKE_INSTALL_BINDIR})
-
 configure_file(cmake/llama.pc.in
         "${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
         @ONLY)

CODEOWNERS

@@ -15,7 +15,7 @@
 # ggml-org/llama-common     : ggerganov, aldehir, angt, danbev, ngxson, pwilkin
 # ggml-org/llama-mtmd       : ngxson
 # ggml-org/llama-server     : ggerganov, ngxson, allozaur, angt, ServeurpersoCom
-# ggml-org/llama-webui      : allozaur
+# ggml-org/llama-ui           : allozaur
 
 /.devops/*.Dockerfile                   @ngxson
 /.github/actions/                       @ggml-org/ci
@@ -26,6 +26,7 @@
 /common/fit.*                           @JohannesGaessler
 /common/jinja/                          @CISC
 /common/ngram-map.*                     @srogmann
+/conversion/                            @CISC
 /convert_*.py                           @CISC
 /docs/backend/snapdragon/               @ggml-org/ggml-hexagon
 /examples/batched.swift/                @ggerganov
@@ -48,7 +49,6 @@
 /examples/parallel/                     @ggerganov
 /examples/passkey/                      @ggerganov
 /examples/retrieval/                    @ggerganov
-/examples/save-load-state/              @ggerganov
 /examples/speculative-simple/           @ggerganov
 /examples/speculative/                  @ggerganov
 /ggml/cmake/                            @ggerganov
@@ -76,6 +76,7 @@
 /ggml/src/ggml-vulkan/                  @ggml-org/ggml-vulkan
 /ggml/src/ggml-webgpu/                  @ggml-org/ggml-webgpu
 /ggml/src/ggml-zdnn/                    @ggml-org/ggml-zdnn @Andreas-Krebbel @AlekseiNikiforovIBM
+/ggml/src/ggml-zendnn/                  @avinashcpandey @Jiten1parmar @z-vishal
 /ggml/src/ggml.c                        @ggerganov
 /ggml/src/ggml.cpp                      @ggerganov
 /ggml/src/gguf.cpp                      @JohannesGaessler @Green-Sky
@@ -106,7 +107,7 @@
 /tools/rpc/                             @ggml-org/ggml-rpc
 /tools/server/*                         @ggml-org/llama-server # no subdir
 /tools/server/tests/                    @ggml-org/llama-server
-/tools/server/webui/                    @ggml-org/llama-webui
+/tools/ui/                              @ggml-org/llama-ui
 /tools/tokenize/                        @ggerganov
 /tools/tts/                             @ggerganov
 /vendor/                                @ggerganov

CONTRIBUTING.md

@@ -46,7 +46,9 @@ Before submitting your PR:
     - provide KL divergence data calculated vs. the FP16/BF16 (whichever is the native precision) version for both the new type as well as types of similar size
     - provide [performance data](https://github.com/ggml-org/llama.cpp/tree/master/tools/llama-bench) for the new type in comparison to types of similar size on pure CPU
 - Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
-- If you are a new contributor, limit your open PRs to 1.
+- If you are a new contributor
+    - Limit your open PRs to 1
+    - Do not submit trivial fixes (e.g. typos, formatting changes)
 
 After submitting your PR:
 - Expect requests for modifications to ensure the code meets llama.cpp's standards for quality and long-term maintainability

README.md

@@ -27,6 +27,7 @@ LLM inference in C/C++
 - Vim/Neovim plugin for FIM completions: https://github.com/ggml-org/llama.vim
 - Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggml-org/llama.cpp/discussions/9669
 - Hugging Face GGUF editor: [discussion](https://github.com/ggml-org/llama.cpp/discussions/9268) | [tool](https://huggingface.co/spaces/CISCai/gguf-editor)
+- WebGPU support is now available in the browser, see a blog/demo introducing it [here](https://reeselevine.github.io/llamas-on-the-web/).
 
 ----
 
@@ -172,6 +173,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 - JavaScript/Wasm (works in browser): [tangledgroup/llama-cpp-wasm](https://github.com/tangledgroup/llama-cpp-wasm)
 - Typescript/Wasm (nicer API, available on npm): [ngxson/wllama](https://github.com/ngxson/wllama)
 - Ruby: [yoshoku/llama_cpp.rb](https://github.com/yoshoku/llama_cpp.rb)
+- Ruby: [docusealco/rllama](https://github.com/docusealco/rllama)
 - Rust (more features): [edgenai/llama_cpp-rs](https://github.com/edgenai/llama_cpp-rs)
 - Rust (nicer API): [mdrokz/rust-llama.cpp](https://github.com/mdrokz/rust-llama.cpp)
 - Rust (more direct bindings): [utilityai/llama-cpp-rs](https://github.com/utilityai/llama-cpp-rs)
@@ -279,7 +281,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 | [Metal](docs/build.md#metal-build) | Apple Silicon |
 | [BLAS](docs/build.md#blas-build) | All |
 | [BLIS](docs/backend/BLIS.md) | All |
-| [SYCL](docs/backend/SYCL.md) | Intel and Nvidia GPU |
+| [SYCL](docs/backend/SYCL.md) | Intel GPU |
 | [OpenVINO [In Progress]](docs/backend/OPENVINO.md) | Intel CPUs, GPUs, and NPUs |
 | [MUSA](docs/build.md#musa) | Moore Threads GPU |
 | [CUDA](docs/build.md#cuda) | Nvidia GPU |
@@ -289,7 +291,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 | [CANN](docs/build.md#cann) | Ascend NPU |
 | [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
 | [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
-| [WebGPU [In Progress]](docs/build.md#webgpu) | All |
+| [WebGPU](docs/build.md#webgpu) | All |
 | [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
 | [Hexagon [In Progress]](docs/backend/snapdragon/README.md) | Snapdragon |
 | [VirtGPU](docs/backend/VirtGPU.md) | VirtGPU APIR |
@@ -529,6 +531,7 @@ To learn more about model quantization, [read this documentation](tools/quantize
 - [How to build](docs/build.md)
 - [Running on Docker](docs/docker.md)
 - [Build on Android](docs/android.md)
+- [Multi-GPU usage](docs/multi-gpu.md)
 - [Performance troubleshooting](docs/development/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggml-org/llama.cpp/wiki/GGML-Tips-&-Tricks)
 

app/CMakeLists.txt

@@ -0,0 +1,20 @@
+set(TARGET llama-app)
+
+add_executable(${TARGET} llama.cpp)
+set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama)
+
+target_link_libraries(${TARGET} PRIVATE
+    llama-server-impl
+    llama-cli-impl
+    llama-completion-impl
+    llama-bench-impl
+    llama-batched-bench-impl
+    llama-fit-params-impl
+    llama-quantize-impl
+    llama-perplexity-impl
+)
+target_compile_features(${TARGET} PRIVATE cxx_std_17)
+
+if(LLAMA_TOOLS_INSTALL)
+    install(TARGETS ${TARGET} RUNTIME)
+endif()

app/llama.cpp

@@ -0,0 +1,95 @@
+#include "build-info.h"
+
+#include <cstdio>
+#include <cstdlib>
+#include <string>
+#include <vector>
+
+// visible
+int llama_server(int argc, char ** argv);
+int llama_cli(int argc, char ** argv);
+
+// hidden
+int llama_completion(int argc, char ** argv);
+int llama_bench(int argc, char ** argv);
+int llama_batched_bench(int argc, char ** argv);
+int llama_fit_params(int argc, char ** argv);
+int llama_quantize(int argc, char ** argv);
+int llama_perplexity(int argc, char ** argv);
+
+static int help(int argc, char ** argv);
+static int version(int argc, char ** argv);
+
+struct command {
+    const char * name;
+    const char * desc;
+    std::vector<std::string> aliases;
+    bool hidden;
+    int (*func)(int, char **);
+};
+
+static const command cmds[] = {
+    {"serve",         "HTTP API server",                                    {"server"},   false, llama_server       },
+    {"cli",           "Command-line interactive interface",                 {"client"},   false, llama_cli          },
+    {"completion",    "Text completion",                                    {"complete"}, true,  llama_completion   },
+    {"bench",         "Benchmark prompt processing and text generation",    {},           true,  llama_bench        },
+    {"batched-bench", "Benchmark batched decoding performance",             {},           true,  llama_batched_bench},
+    {"fit-params",    "Compute parameters to fit a model in device memory", {},           true,  llama_fit_params   },
+    {"quantize",      "Quantize a model",                                   {},           true,  llama_quantize     },
+    {"perplexity",    "Compute model perplexity and KL divergence",         {},           true,  llama_perplexity   },
+    {"version",       "Show version",                                       {},           true,  version            },
+    {"help",          "Show available commands",                            {},           true,  help               },
+};
+
+static int version(int argc, char ** argv) {
+    printf("%s\n", llama_build_info());
+    return 0;
+}
+
+static int help(int argc, char ** argv) {
+    const bool show_all = argc >= 2 && std::string(argv[1]) == "all";
+
+    printf("Usage: llama <command> [options]\n\nAvailable commands:\n");
+
+    for (const auto & cmd : cmds) {
+        if (show_all || !cmd.hidden) {
+            printf("  %-15s %s\n", cmd.name, cmd.desc);
+        }
+    }
+    printf("\nRun 'llama <command> --help' for command-specific usage.\n");
+
+    return 0;
+}
+
+static bool matches(const std::string & arg, const command & cmd) {
+    if (arg == cmd.name) {
+        return true;
+    }
+    for (const auto & alias : cmd.aliases) {
+        if (arg == alias) {
+            return true;
+        }
+    }
+    return false;
+}
+
+int main(int argc, char ** argv) {
+    const std::string arg = argc >= 2 ? argv[1] : "help";
+
+    for (const auto & cmd : cmds) {
+        if (matches(arg, cmd)) {
+
+            // router spawns children through this same binary, it needs the
+            // subcommand to relaunch as 'llama serve' and not bare options
+#ifdef _WIN32
+            _putenv_s("LLAMA_APP_CMD", cmd.name);
+#else
+            setenv("LLAMA_APP_CMD", cmd.name, 1);
+#endif
+            return cmd.func(argc - 1, argv + 1);
+        }
+    }
+
+    fprintf(stderr, "error: unknown command '%s'\n", arg.c_str());
+    return 1;
+}

build-xcframework.sh

@@ -7,6 +7,7 @@ VISIONOS_MIN_OS_VERSION=1.0
 TVOS_MIN_OS_VERSION=16.4
 
 BUILD_SHARED_LIBS=OFF
+LLAMA_BUILD_APP=OFF
 LLAMA_BUILD_EXAMPLES=OFF
 LLAMA_BUILD_TOOLS=OFF
 LLAMA_BUILD_TESTS=OFF
@@ -31,6 +32,7 @@ COMMON_CMAKE_ARGS=(
     -DCMAKE_XCODE_ATTRIBUTE_STRIP_INSTALLED_PRODUCT=NO
     -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
     -DBUILD_SHARED_LIBS=${BUILD_SHARED_LIBS}
+    -DLLAMA_BUILD_APP=${LLAMA_BUILD_APP}
     -DLLAMA_BUILD_EXAMPLES=${LLAMA_BUILD_EXAMPLES}
     -DLLAMA_BUILD_TOOLS=${LLAMA_BUILD_TOOLS}
     -DLLAMA_BUILD_TESTS=${LLAMA_BUILD_TESTS}

ci/run.sh

@@ -117,6 +117,12 @@ if [ ! -z ${GG_BUILD_VULKAN} ]; then
     # if on Mac, disable METAL
     if [[ "$OSTYPE" == "darwin"* ]]; then
         CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=OFF -DGGML_BLAS=OFF"
+
+        MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION="/usr/local/lib/cmake/vulkan"
+        MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION="${MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION}/SPIRV-Headers/SPIRV-HeadersConfig.cmake"
+        if [[ -f "${MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION}" || -h "${MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION}" ]]; then
+            CMAKE_EXTRA="${CMAKE_EXTRA} -DSPIRV-Headers_DIR=${MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION}/SPIRV-Headers"
+        fi
     fi
 
     # Build shared libs on Windows
@@ -232,7 +238,7 @@ function gg_run_ctest_debug {
     (cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time cmake --build . --config Debug -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    (time ctest -C Debug --output-on-failure -L main -E "test-opt|test-backend-ops" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
+    (time ctest -C Debug --output-on-failure -L main -E "test-opt|test-backend-ops|test-llama-archs" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
 
     set +e
 }
@@ -455,10 +461,10 @@ function gg_run_qwen3_0_6b {
 
     (time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
 
-    (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa off --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
-    (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa on  --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
-    (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa off                ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
-    (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa on                 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/test-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa off --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/test-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa on  --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/test-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa off                ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/test-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa on                 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
 
     function check_ppl {
         qnt="$1"

cmake/llama-config.cmake.in

@@ -7,7 +7,7 @@ set(LLAMA_SHARED_LIB   @BUILD_SHARED_LIBS@)
 
 set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@")
 set_and_check(LLAMA_LIB_DIR     "@PACKAGE_LLAMA_LIB_INSTALL_DIR@")
-set_and_check(LLAMA_BIN_DIR     "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
+set(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
 
 find_package(ggml REQUIRED HINTS ${LLAMA_LIB_DIR}/cmake)
 

cmake/riscv64-spacemit-linux-gnu-gcc.cmake

@@ -24,6 +24,6 @@ set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
 set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)
 set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)
 set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)
-set(CMAKE_C_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CMAKE_C_FLAGS}")
-set(CMAKE_CXX_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CXX_FLAGS}")
+set(CMAKE_C_FLAGS "-march=rv64gcv_zfh_zvfh_zba_zicbop -mabi=lp64d -fno-tree-vectorize -fno-tree-loop-vectorize ${CMAKE_C_FLAGS}")
+set(CMAKE_CXX_FLAGS "-march=rv64gcv_zfh_zvfh_zba_zicbop -mabi=lp64d -fno-tree-vectorize -fno-tree-loop-vectorize ${CMAKE_CXX_FLAGS}")
 set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -latomic")

common/arg.cpp

@@ -4,7 +4,6 @@
 #include "chat.h"
 #include "common.h"
 #include "download.h"
-#include "hf-cache.h"
 #include "json-schema-to-grammar.h"
 #include "log.h"
 #include "sampling.h"
@@ -248,6 +247,8 @@ std::vector<std::string> common_arg::get_env() const {
 
 // Helper function to parse tensor buffer override strings
 static void parse_tensor_buffer_overrides(const std::string & value, std::vector<llama_model_tensor_buft_override> & overrides) {
+    ggml_backend_load_all();
+
     std::map<std::string, ggml_backend_buffer_type_t> buft_list;
     for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
         auto * dev = ggml_backend_dev_get(i);
@@ -306,12 +307,14 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
     common_download_opts opts;
     opts.bearer_token = params.hf_token;
     opts.offline = params.offline;
+
+    LOG_TRC("%s: looking for remote preset at %s\n", __func__, preset_url.c_str());
     const int status = common_download_file_single(preset_url, preset_path, opts);
     const bool has_preset = status >= 200 && status < 400;
 
     // remote preset is optional, so we don't error out if not found
     if (has_preset) {
-        LOG_INF("applying remote preset from %s\n", preset_url.c_str());
+        LOG_TRC("%s: applying remote preset from %s\n", __func__, preset_url.c_str());
         common_preset_context ctx(ex, /* only_remote_allowed */ true);
         common_preset global;
         auto remote_presets = ctx.load_from_ini(preset_path, global);
@@ -324,7 +327,7 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
             throw std::runtime_error("Remote preset.ini does not contain [" + std::string(hf_tag) + "] section");
         }
     } else {
-        LOG_INF("%s", "no remote preset found, skipping\n");
+        LOG_TRC("%s: no remote preset found, skipping\n", __func__);
     }
 
     return has_preset;
@@ -333,11 +336,15 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
 struct handle_model_result {
     bool found_mmproj = false;
     common_params_model mmproj;
+
+    bool found_mtp = false;
+    common_params_model mtp;
 };
 
 static handle_model_result common_params_handle_model(struct common_params_model & model,
                                                       const std::string          & bearer_token,
-                                                      bool                         offline) {
+                                                      bool                         offline,
+                                                      bool                         search_mtp = false) {
     handle_model_result result;
 
     if (!model.docker_repo.empty()) {
@@ -352,11 +359,10 @@ static handle_model_result common_params_handle_model(struct common_params_model
         common_download_opts opts;
         opts.bearer_token = bearer_token;
         opts.offline = offline;
-        auto download_result = common_download_model(model, opts, true);
+        auto download_result = common_download_model(model, opts, true, search_mtp);
 
         if (download_result.model_path.empty()) {
-            LOG_ERR("error: failed to download model from Hugging Face\n");
-            exit(1);
+            throw std::runtime_error("failed to download model from Hugging Face");
         }
 
         model.name = model.hf_repo;
@@ -366,6 +372,11 @@ static handle_model_result common_params_handle_model(struct common_params_model
             result.found_mmproj = true;
             result.mmproj.path  = download_result.mmproj_path;
         }
+
+        if (!download_result.mtp_path.empty()) {
+            result.found_mtp = true;
+            result.mtp.path  = download_result.mtp_path;
+        }
     } else if (!model.url.empty()) {
         if (model.path.empty()) {
             auto f = string_split<std::string>(model.url, '#').front();
@@ -378,8 +389,7 @@ static handle_model_result common_params_handle_model(struct common_params_model
         opts.offline = offline;
         auto download_result = common_download_model(model, opts);
         if (download_result.model_path.empty()) {
-            LOG_ERR("error: failed to download model from %s\n", model.url.c_str());
-            exit(1);
+            throw std::runtime_error("failed to download model from " + model.url);
         }
     }
 
@@ -425,10 +435,45 @@ static bool parse_bool_value(const std::string & value) {
     }
 }
 
+[[noreturn]] static void arg_removed(const std::string & msg) {
+    throw std::invalid_argument("the argument has been removed. " + msg);
+}
+
 //
 // CLI argument parsing functions
 //
 
+void common_params_handle_models(common_params & params, llama_example curr_ex) {
+    const bool spec_type_draft_mtp = std::find(params.speculative.types.begin(),
+                                         params.speculative.types.end(),
+                                         COMMON_SPECULATIVE_TYPE_DRAFT_MTP) != params.speculative.types.end();
+
+    auto res = common_params_handle_model(params.model, params.hf_token, params.offline, spec_type_draft_mtp);
+    if (params.no_mmproj) {
+        params.mmproj = {};
+    } else if (res.found_mmproj && params.mmproj.path.empty() && params.mmproj.url.empty()) {
+        // optionally, handle mmproj model when -hf is specified
+        params.mmproj = res.mmproj;
+    }
+    // only download mmproj if the current example is using it
+    for (const auto & ex : mmproj_examples) {
+        if (curr_ex == ex) {
+            common_params_handle_model(params.mmproj,    params.hf_token, params.offline);
+            break;
+        }
+    }
+    // when --spec-type mtp is set and no draft model was provided explicitly,
+    // fall back to the MTP head discovered alongside the -hf model
+    if (spec_type_draft_mtp && res.found_mtp &&
+        params.speculative.draft.mparams.path.empty() &&
+        params.speculative.draft.mparams.hf_repo.empty() &&
+        params.speculative.draft.mparams.url.empty()) {
+        params.speculative.draft.mparams.path = res.mtp.path;
+    }
+    common_params_handle_model(params.speculative.draft.mparams, params.hf_token, params.offline);
+    common_params_handle_model(params.vocoder.model,             params.hf_token, params.offline);
+}
+
 static bool common_params_parse_ex(int argc, char ** argv, common_params_context & ctx_arg) {
     common_params & params = ctx_arg.params;
 
@@ -491,7 +536,11 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
                 throw std::invalid_argument(string_format("error: invalid argument: %s", arg.c_str()));
             }
             if (!seen_args.insert(arg).second) {
-                LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
+                const bool skip = (arg == "--spec-type");
+
+                if (!skip) {
+                    LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
+                }
             }
             auto & tmp = arg_to_options[arg];
             auto opt = *tmp.first;
@@ -540,12 +589,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
     // parse the first time to get -hf option (used for remote preset)
     parse_cli_args();
 
-    // TODO: Remove later
-    try {
-        hf_cache::migrate_old_cache_to_hf_cache(params.hf_token, params.offline);
-    } catch (const std::exception & e) {
-        LOG_WRN("HF cache migration failed: %s\n", e.what());
-    }
     // export_graph_ops loads only metadata
     const bool skip_model_download = ctx_arg.ex == LLAMA_EXAMPLE_EXPORT_GRAPH_OPS;
 
@@ -582,22 +625,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
 
     // handle model and download
     if (!skip_model_download) {
-        auto res = common_params_handle_model(params.model, params.hf_token, params.offline);
-        if (params.no_mmproj) {
-            params.mmproj = {};
-        } else if (res.found_mmproj && params.mmproj.path.empty() && params.mmproj.url.empty()) {
-            // optionally, handle mmproj model when -hf is specified
-            params.mmproj = res.mmproj;
-        }
-        // only download mmproj if the current example is using it
-        for (const auto & ex : mmproj_examples) {
-            if (ctx_arg.ex == ex) {
-                common_params_handle_model(params.mmproj,    params.hf_token, params.offline);
-                break;
-            }
-        }
-        common_params_handle_model(params.speculative.draft.mparams, params.hf_token, params.offline);
-        common_params_handle_model(params.vocoder.model,             params.hf_token, params.offline);
+        common_params_handle_models(params, ctx_arg.ex);
     }
 
     // model is required (except for server)
@@ -616,10 +644,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
         for (auto & seq_breaker : params.sampling.dry_sequence_breakers) {
             string_process_escapes(seq_breaker);
         }
-        for (auto & pair : params.speculative.draft.replacements) {
-            string_process_escapes(pair.first);
-            string_process_escapes(pair.second);
-        }
     }
 
     if (!params.kv_overrides.empty()) {
@@ -803,6 +827,7 @@ static std::vector<ggml_backend_dev_t> parse_device_list(const std::string & val
     if (dev_names.size() == 1 && dev_names[0] == "none") {
         devices.push_back(nullptr);
     } else {
+        ggml_backend_load_all();
         for (const auto & device : dev_names) {
             auto * dev = ggml_backend_dev_by_name(device.c_str());
             if (!dev || ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_CPU) {
@@ -820,6 +845,7 @@ static void add_rpc_devices(const std::string & servers) {
     if (rpc_servers.empty()) {
         throw std::invalid_argument("no RPC servers specified");
     }
+    ggml_backend_load_all();
     ggml_backend_reg_t rpc_reg = ggml_backend_reg_by_name("RPC");
     if (!rpc_reg) {
         throw std::invalid_argument("failed to find RPC backend");
@@ -871,7 +897,11 @@ bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<com
             throw std::invalid_argument(string_format("error: invalid argument: %s", arg.c_str()));
         }
         if (!seen_args.insert(arg).second) {
-            LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
+            const bool skip = (arg == "--spec-type");
+
+            if (!skip) {
+                LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
+            }
         }
         auto opt = *arg_to_options[arg];
         std::string val;
@@ -1016,9 +1046,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
 
     params.use_color = tty_can_use_colors();
 
-    // load dynamic backends
-    ggml_backend_load_all();
-
     common_params_context ctx_arg(params);
     ctx_arg.print_usage = print_usage;
     ctx_arg.ex          = ex;
@@ -1307,12 +1334,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_env("LLAMA_ARG_CTX_CHECKPOINTS").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
     add_opt(common_arg(
-        {"-cpent", "--checkpoint-every-n-tokens"}, "N",
-        string_format("create a checkpoint every n tokens during prefill (processing), -1 to disable (default: %d)", params.checkpoint_every_nt),
+        {"-cms", "--checkpoint-min-step"}, "N",
+        string_format("minimum spacing between context checkpoints in tokens (default: %d, 0 = no minimum)", params.checkpoint_min_step),
         [](common_params & params, int value) {
-            params.checkpoint_every_nt = value;
+            if (value < 0) {
+                throw std::invalid_argument("checkpoint-min-step must be non-negative");
+            }
+            params.checkpoint_min_step = value;
         }
-    ).set_env("LLAMA_ARG_CHECKPOINT_EVERY_NT").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
+    ).set_env("LLAMA_ARG_CHECKPOINT_MIN_SPACING_NT").set_examples({LLAMA_EXAMPLE_SERVER}));
     add_opt(common_arg(
         {"-cram", "--cache-ram"}, "N",
         string_format("set the maximum cache size in MiB (default: %d, -1 - no limit, 0 - disable)"
@@ -2218,7 +2248,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     if (llama_supports_rpc()) {
         add_opt(common_arg(
             {"--rpc"}, "SERVERS",
-            "comma separated list of RPC servers (host:port)",
+            "comma-separated list of RPC servers (host:port)",
             [](common_params & params, const std::string & value) {
                 add_rpc_devices(value);
                 GGML_UNUSED(params);
@@ -2275,6 +2305,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         {"--list-devices"},
         "print list of available devices and exit",
         [](common_params &) {
+            ggml_backend_load_all();
             std::vector<ggml_backend_dev_t> devices;
             for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
                 auto * dev = ggml_backend_dev_get(i);
@@ -2781,7 +2812,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         [](common_params & params, int value) {
             params.embd_normalize = value;
         }
-    ).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_DEBUG}));
+    ).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_DEBUG}));
     add_opt(common_arg(
         {"--embd-output-format"}, "FORMAT",
         "empty = default, \"array\" = [[],[]...], \"json\" = openai style, \"json+\" = same \"json\" + cosine similarity matrix, \"raw\" = plain whitespace-delimited output (one embedding per line)",
@@ -2838,45 +2869,93 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.api_prefix = value;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_API_PREFIX"));
+    // Deprecated: use --ui-config instead (kept for backward compat)
     add_opt(common_arg(
         {"--webui-config"}, "JSON",
-        "JSON that provides default WebUI settings (overrides WebUI defaults)",
+        "[DEPRECATED: use --ui-config] JSON that provides default WebUI settings (overrides WebUI defaults)",
         [](common_params & params, const std::string & value) {
+            params.ui_config_json = value;
             params.webui_config_json = value;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG"));
+
+    add_opt(common_arg(
+        {"--ui-config"}, "JSON",
+        "JSON that provides default UI settings (overrides UI defaults)",
+        [](common_params & params, const std::string & value) {
+            params.ui_config_json = value;
+            params.webui_config_json = value;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG"));
+
+    // Deprecated: use --ui-config-file instead (kept for backward compat)
     add_opt(common_arg(
         {"--webui-config-file"}, "PATH",
-        "JSON file that provides default WebUI settings (overrides WebUI defaults)",
+        "[DEPRECATED: use --ui-config-file] JSON file that provides default WebUI settings (overrides WebUI defaults)",
         [](common_params & params, const std::string & value) {
-            params.webui_config_json = read_file(value);
+            params.ui_config_json = read_file(value);
+            params.webui_config_json = params.ui_config_json;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG_FILE"));
+
+    add_opt(common_arg(
+        {"--ui-config-file"}, "PATH",
+        "JSON file that provides default UI settings (overrides UI defaults)",
+        [](common_params & params, const std::string & value) {
+            params.ui_config_json = read_file(value);
+            params.webui_config_json = params.ui_config_json;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG_FILE"));
+
+    // Deprecated: use --ui-mcp-proxy instead (kept for backward compat)
     add_opt(common_arg(
         {"--webui-mcp-proxy"},
         {"--no-webui-mcp-proxy"},
-        string_format("experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: %s)", params.webui_mcp_proxy ? "enabled" : "disabled"),
+        "[DEPRECATED: use --ui-mcp-proxy/--no-ui-mcp-proxy] experimental: whether to enable MCP CORS proxy",
         [](common_params & params, bool value) {
+            params.ui_mcp_proxy = value;
             params.webui_mcp_proxy = value;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_MCP_PROXY"));
+
+    add_opt(common_arg(
+        {"--ui-mcp-proxy"},
+        {"--no-ui-mcp-proxy"},
+        "experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)",
+        [](common_params & params, bool value) {
+            params.ui_mcp_proxy = value;
+            params.webui_mcp_proxy = value;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_MCP_PROXY"));
     add_opt(common_arg(
         {"--tools"}, "TOOL1,TOOL2,...",
         "experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)\n"
         "specify \"all\" to enable all tools\n"
-        "available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, apply_diff",
+        "available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, apply_diff, get_datetime",
         [](common_params & params, const std::string & value) {
             params.server_tools = parse_csv_row(value);
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS"));
+    // Deprecated: use --ui/--no-ui instead (kept for backward compat)
     add_opt(common_arg(
         {"--webui"},
         {"--no-webui"},
-        string_format("whether to enable the Web UI (default: %s)", params.webui ? "enabled" : "disabled"),
+        "[DEPRECATED: use --ui/--no-ui] whether to enable the Web UI",
         [](common_params & params, bool value) {
+            params.ui = value;
             params.webui = value;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI"));
+
+    add_opt(common_arg(
+        {"--ui"},
+        {"--no-ui"},
+        string_format("whether to enable the Web UI (default: %s)", params.ui ? "enabled" : "disabled"),
+        [](common_params & params, bool value) {
+            params.ui = value;
+            params.webui = value;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI"));
     add_opt(common_arg(
         {"--embedding", "--embeddings"},
         string_format("restrict to only support embedding use case; use only with dedicated embedding models (default: %s)", params.embedding ? "enabled" : "disabled"),
@@ -3288,7 +3367,8 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             " - 1: error\n"
             " - 2: warning\n"
             " - 3: info\n"
-            " - 4: debug\n"
+            " - 4: trace (more info)\n"
+            " - 5: debug\n"
             "(default: %d)\n", params.verbosity),
         [](common_params & params, int value) {
             params.verbosity = value;
@@ -3297,18 +3377,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_env("LLAMA_LOG_VERBOSITY"));
     add_opt(common_arg(
         {"--log-prefix"},
+        {"--no-log-prefix"},
         "Enable prefix in log messages",
-        [](common_params &) {
-            common_log_set_prefix(common_log_main(), true);
+        [](common_params &, bool value) {
+            common_log_set_prefix(common_log_main(), value);
         }
-    ).set_env("LLAMA_LOG_PREFIX"));
+    ).set_env("LLAMA_ARG_LOG_PREFIX"));
     add_opt(common_arg(
         {"--log-timestamps"},
+        {"--no-log-timestamps"},
         "Enable timestamps in log messages",
-        [](common_params &) {
-            common_log_set_timestamps(common_log_main(), true);
+        [](common_params &, bool value) {
+            common_log_set_timestamps(common_log_main(), value);
         }
-    ).set_env("LLAMA_LOG_TIMESTAMPS"));
+    ).set_env("LLAMA_ARG_LOG_TIMESTAMPS"));
 
     //
     // speculative parameters
@@ -3380,7 +3462,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
     add_opt(common_arg(
         {"--spec-draft-poll", "--poll-draft"}, "<0|1>",
-        "Use polling to wait for draft model work (default: same as --poll])",
+        "Use polling to wait for draft model work (default: same as --poll)",
         [](common_params & params, int value) {
             params.speculative.draft.cpuparams.poll = value;
         }
@@ -3499,7 +3581,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_N_MIN"));
 
     add_opt(common_arg(
-        {"--spec--draft-p-split", "--draft-p-split"}, "P",
+        {"--spec-draft-p-split", "--draft-p-split"}, "P",
         string_format("speculative decoding split probability (default: %.2f)", (double)params.speculative.draft.p_split),
         [](common_params & params, const std::string & value) {
             params.speculative.draft.p_split = std::stof(value);
@@ -3513,12 +3595,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_P_MIN"));
     add_opt(common_arg(
-        {"--spec-draft-ctx-size", "-cd", "--ctx-size-draft"}, "N",
-        string_format("size of the prompt context for the draft model (default: %d, 0 = loaded from model)", params.speculative.draft.n_ctx),
-        [](common_params & params, int value) {
-            params.speculative.draft.n_ctx = value;
+        {"--spec-draft-backend-sampling"},
+        {"--no-spec-draft-backend-sampling"},
+        string_format("offload draft sampling to the backend (default: %s)",
+                      params.speculative.draft.backend_sampling ? "enabled" : "disabled"),
+        [](common_params & params, bool value) {
+            params.speculative.draft.backend_sampling = value;
         }
-    ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_CTX_SIZE"));
+    ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_BACKEND_SAMPLING"));
     add_opt(common_arg(
         {"--spec-draft-device", "-devd", "--device-draft"}, "<dev1,dev2,..>",
         "comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
@@ -3555,32 +3639,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_MODEL"));
     add_opt(common_arg(
-        {"--spec-draft-replace", "--spec-replace"}, "TARGET", "DRAFT",
-        "translate the string in TARGET into DRAFT if the draft model and main model are not compatible",
-        [](common_params & params, const std::string & tgt, const std::string & dft) {
-            params.speculative.draft.replacements.push_back({ tgt, dft });
-        }
-    ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
-    add_opt(common_arg(
-        {"--spec-type"}, "[none|ngram-cache|ngram-simple|ngram-map-k|ngram-map-k4v|ngram-mod]",
-        string_format("type of speculative decoding to use when no draft model is provided (default: %s)\n",
-            common_speculative_type_to_str(params.speculative.type).c_str()),
+        {"--spec-type"}, common_speculative_all_types_str(),
+        string_format("comma-separated list of types of speculative decoding to use (default: %s)\n",
+            common_speculative_type_name_str(params.speculative.types).c_str()),
         [](common_params & params, const std::string & value) {
-            if (value == "none") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NONE;
-            } else if (value == "ngram-cache") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_CACHE;
-            } else if (value == "ngram-simple") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE;
-            } else if (value == "ngram-map-k") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K;
-            } else if (value == "ngram-map-k4v") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V;
-            } else if (value == "ngram-mod") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
-            } else {
-                throw std::invalid_argument("unknown speculative decoding type without draft model");
-            }
+            const auto types_str = string_split<std::string>(value, ',');
+            auto types = common_speculative_types_from_names(types_str);
+            params.speculative.types.insert(params.speculative.types.end(), types.begin(), types.end());
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_TYPE"));
     add_opt(common_arg(
@@ -3715,35 +3780,35 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         {"--draft", "--draft-n", "--draft-max"}, "N",
         "the argument has been removed. use --spec-draft-n-max or --spec-ngram-mod-n-max",
         [](common_params & /*params*/, int /*value*/) {
-            throw std::invalid_argument("the argument has been removed. use --spec-draft-n-max or --spec-ngram-mod-n-max");
+            arg_removed("use --spec-draft-n-max or --spec-ngram-mod-n-max");
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_MAX"));
     add_opt(common_arg(
         {"--draft-min", "--draft-n-min"}, "N",
         "the argument has been removed. use --spec-draft-n-min or --spec-ngram-mod-n-min",
         [](common_params & /*params*/, int /*value*/) {
-            throw std::invalid_argument("the argument has been removed. use --spec-draft-n-min or --spec-ngram-mod-n-min");
+            arg_removed("use --spec-draft-n-min or --spec-ngram-mod-n-min");
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_MIN"));
     add_opt(common_arg(
         {"--spec-ngram-size-n"}, "N",
         "the argument has been removed. use the respective --spec-ngram-*-size-n or --spec-ngram-mod-n-match",
         [](common_params & /*params*/, int /*value*/) {
-            throw std::invalid_argument("the argument has been removed. use the respective --spec-ngram-*-size-n");
+            arg_removed("use the respective --spec-ngram-*-size-n");
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SERVER}));
     add_opt(common_arg(
         {"--spec-ngram-size-m"}, "N",
         "the argument has been removed. use the respective --spec-ngram-*-size-m",
         [](common_params & /*params*/, int /*value*/) {
-            throw std::invalid_argument("the argument has been removed. use the respective --spec-ngram-*-size-m");
+            arg_removed("use the respective --spec-ngram-*-size-m");
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SERVER}));
     add_opt(common_arg(
         {"--spec-ngram-min-hits"}, "N",
         "the argument has been removed. use the respective --spec-ngram-*-min-hits",
         [](common_params & /*params*/, int /*value*/) {
-            throw std::invalid_argument("the argument has been removed. use the respective --spec-ngram-*-min-hits");
+            arg_removed("use the respective --spec-ngram-*-min-hits");
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SERVER}));
 
@@ -3794,7 +3859,10 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
     add_opt(common_arg(
         {"--diffusion-algorithm"}, "N",
-        string_format("diffusion algorithm: 0=ORIGIN, 1=ENTROPY_BASED, 2=MARGIN_BASED, 3=RANDOM, 4=LOW_CONFIDENCE (default: %d)", params.diffusion.algorithm),
+        string_format(
+            "diffusion algorithm: 0=DIFFUSION_ALGORITHM_ORIGIN, 1=DIFFUSION_ALGORITHM_ENTROPY_BASED, "
+            "2=DIFFUSION_ALGORITHM_MARGIN_BASED, 3=DIFFUSION_ALGORITHM_RANDOM, "
+            "4=DIFFUSION_ALGORITHM_CONFIDENCE_BASED (default: %d)", params.diffusion.algorithm),
         [](common_params & params, int value) { params.diffusion.algorithm = value; }
     ).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
     add_opt(common_arg(
@@ -4066,10 +4134,16 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         {"--spec-default"},
         string_format("enable default speculative decoding config"),
         [](common_params & params) {
-            params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
+            params.speculative.types.push_back(COMMON_SPECULATIVE_TYPE_NGRAM_MOD);
             params.speculative.ngram_mod.n_match = 24;
             params.speculative.ngram_mod.n_min = 48;
             params.speculative.ngram_mod.n_max = 64;
+
+            // TODO: not sure if this is a good config - explore more settings and potentially enable it
+            //params.speculative.types.push_back(COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V);
+            //params.speculative.ngram_map_k4v.size_n = 8;
+            //params.speculative.ngram_map_k4v.size_m = 24;
+            //params.speculative.ngram_map_k4v.min_hits = 2;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
 

common/arg.h

@@ -129,5 +129,8 @@ bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<com
 // see: https://github.com/ggml-org/llama.cpp/issues/18163
 void common_params_add_preset_options(std::vector<common_arg> & args);
 
+// Populate model paths (main model, mmproj, etc) from -hf if necessary
+void common_params_handle_models(common_params & params, llama_example curr_ex);
+
 // initialize argument parser context - used by test-arg-parser and preset
 common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);

common/chat-auto-parser-generator.cpp

@@ -43,11 +43,33 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
                                                   const autoparser &              autoparser) {
     // Create the result structure
     common_chat_params data;
-    data.prompt           = common_chat_template_direct_apply(tmpl, inputs);
-    data.format           = COMMON_CHAT_FORMAT_PEG_NATIVE;
-    data.preserved_tokens = autoparser.preserved_tokens;
+    data.prompt            = common_chat_template_direct_apply(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt(tmpl, inputs);
+    data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.preserved_tokens  = autoparser.preserved_tokens;
 
-    auto parser = autoparser.build_parser(inputs);
+    std::string parser_generation_prompt = data.generation_prompt;
+
+    if (inputs.continue_final_message != COMMON_CHAT_CONTINUATION_NONE && !inputs.continue_msg.empty()) {
+        // Build up generation prompt manually
+        const auto & msg = inputs.continue_msg;
+
+        if (!autoparser.reasoning.start.empty()) {
+            data.generation_prompt = data.generation_prompt.substr(0, data.generation_prompt.find(autoparser.reasoning.start));
+            data.generation_prompt += autoparser.reasoning.start + msg.reasoning_content;
+            if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+                data.generation_prompt += autoparser.reasoning.end;
+            }
+        }
+
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
+    auto parser = autoparser.build_parser(inputs, parser_generation_prompt);
     data.parser = parser.save();
 
     // Build grammar if tools are present
@@ -87,7 +109,7 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
     return data;
 }
 
-common_peg_arena autoparser::build_parser(const generation_params & inputs) const {
+common_peg_arena autoparser::build_parser(const generation_params & inputs, const std::string & generation_prompt) const {
     if (!analysis_complete) {
         throw std::invalid_argument("Cannot call build_parser on autoparser without performing analysis first, call analyze_template(...)");
     }
@@ -121,7 +143,7 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs) cons
         } else {
             parser = content.build_parser(ctx);
         }
-        return pure_content ? p.prefix(inputs.generation_prompt, reasoning.start) + parser : p.prefix(inputs.generation_prompt, reasoning.start) << parser;
+        return pure_content ? p.prefix(generation_prompt, reasoning.start) + parser : p.prefix(generation_prompt, reasoning.start) << parser;
     });
 }
 
@@ -136,10 +158,10 @@ common_peg_parser analyze_reasoning::build_parser(parser_build_context & ctx) co
         if (!end.empty()) {
             if (!start.empty()) {
                 // Standard tag-based: optional(<think>reasoning</think>)
-                return p.optional(start + p.reasoning(p.until(end)) + end + p.space());
+                return p.optional(p.optspace(start) + p.reasoning(p.until(trim_whitespace(end))) + p.optspace(end));
             }
             // Delimiter-style (empty start)
-            return p.optional(p.reasoning(p.until(end)) + end + p.space());
+            return p.optional(p.reasoning(p.until(trim_whitespace(end))) + p.optspace(end));
         }
     }
 
@@ -186,7 +208,6 @@ common_peg_parser analyze_tools::build_parser(parser_build_context & ctx) const
 common_peg_parser analyze_tools::build_tool_parser_json_native(parser_build_context & ctx) const {
     auto &       p           = ctx.p;
     const auto & inputs      = ctx.inputs;
-    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
 
     // Build effective field names with dot notation if function_field is set
     std::string name_field = format.name_field;
@@ -225,8 +246,7 @@ common_peg_parser analyze_tools::build_tool_parser_json_native(parser_build_cont
         tool_start = format.per_call_start;
     }
 
-    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(p.until(tool_start)))) + tools_parser +
-           p.end();
+    return ctx.reasoning_parser + p.optional(p.content(p.until(tool_start))) + tools_parser + p.end();
 }
 
 common_peg_parser analyze_tools::build_func_parser(common_chat_peg_builder & p, const std::string & name,
@@ -270,7 +290,6 @@ common_peg_parser analyze_tools::build_func_parser(common_chat_peg_builder & p,
 common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context & ctx) const {
     auto &       p           = ctx.p;
     const auto & inputs      = ctx.inputs;
-    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
 
     common_peg_parser tool_choice = p.choice();
 
@@ -336,14 +355,12 @@ common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context
 
     std::string trigger_marker       = !format.section_start.empty() ? format.section_start : format.per_call_start;
     auto        content_before_tools = trigger_marker.empty() ? p.eps() : p.until(trigger_marker);
-    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(content_before_tools))) + tool_calls +
-           p.end();
+    return ctx.reasoning_parser + p.optional(p.content(content_before_tools)) + tool_calls + p.end();
 }
 
 common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_context & ctx) const {
     auto &       p           = ctx.p;
     const auto & inputs      = ctx.inputs;
-    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
 
     auto until_suffix = p.rule("until-suffix", p.until(arguments.value_suffix));
 
@@ -374,9 +391,7 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
                                            arguments.name_suffix) +
                            arguments.value_prefix +
                            (schema_info.resolves_to_string(param_schema) ?
-                                p.tool_arg_string_value(p.schema(until_suffix,
-                                                                 "tool-" + name + "-arg-" + param_name + "-schema",
-                                                                 param_schema, true)) :
+                                p.tool_arg_string_value(until_suffix) :
                                 p.tool_arg_json_value(p.schema(
                                     p.json(), "tool-" + name + "-arg-" + param_name + "-schema", param_schema, false)) +
                                     p.space()) +
@@ -471,8 +486,7 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
 
     std::string trigger_marker       = !format.section_start.empty() ? format.section_start : format.per_call_start;
     auto        content_before_tools = trigger_marker.empty() ? p.eps() : p.until(trigger_marker);
-    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(content_before_tools))) + tool_calls +
-           p.end();
+    return ctx.reasoning_parser + p.optional(p.content(content_before_tools)) + tool_calls + p.end();
 }
 
 }  // namespace autoparser

common/chat-auto-parser-helpers.cpp

@@ -310,6 +310,8 @@ std::vector<segment> prune_whitespace_segments(const std::vector<segment> & segm
 
 namespace autoparser {
 
+static const std::string ERR_TMPL = "#**ERROR**#";
+
 std::string apply_template(const common_chat_template & tmpl, const template_params & params) {
     generation_params tmpl_params;
     tmpl_params.messages              = params.messages;
@@ -326,7 +328,7 @@ std::string apply_template(const common_chat_template & tmpl, const template_par
         return common_chat_template_direct_apply(tmpl, tmpl_params);
     } catch (const std::exception & e) {
         LOG_DBG("Template application failed: %s\n", e.what());
-        return "";
+        return ERR_TMPL;
     }
 }
 
@@ -347,7 +349,7 @@ std::optional<compare_variants_result> compare_variants(
     std::string output_B = apply_template(tmpl, params_B);
 
     // Check for template application failures
-    if (output_A.empty() || output_B.empty()) {
+    if (output_A == ERR_TMPL || output_B == ERR_TMPL) {
         return std::nullopt;
     }
 

common/chat-auto-parser.h

@@ -60,16 +60,21 @@ struct generation_params {
     common_reasoning_format               reasoning_format    = COMMON_REASONING_FORMAT_AUTO;
     bool                                  stream              = true;
     std::string                           grammar;
-    bool                                  add_generation_prompt = false;
-    bool                                  enable_thinking       = true;
-    std::chrono::system_clock::time_point now                   = std::chrono::system_clock::now();
-    std::string                           generation_prompt;
+    bool                                  add_generation_prompt  = false;
+    common_chat_continuation              continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
+    common_chat_msg                       continue_msg;
+    bool                                  enable_thinking        = true;
+    std::chrono::system_clock::time_point now                    = std::chrono::system_clock::now();
     json                                  extra_context;
     bool                                  add_bos       = false;
     bool                                  add_eos       = false;
     bool                                  is_inference  = true;
     bool                                  add_inference = false;
     bool                                  mark_input    = true;  // whether to mark input strings in the jinja context
+
+    bool has_continuation() const {
+        return continue_final_message != COMMON_CHAT_CONTINUATION_NONE && !continue_msg.empty();
+    }
 };
 
 // ============================================================================
@@ -372,6 +377,8 @@ struct analyze_tools : analyze_base {
 
 struct autoparser {
     jinja::caps          jinja_caps;
+    std::string          user_start;
+    std::string          assistant_start;
     analyze_reasoning    reasoning;
     analyze_content      content;
     analyze_tools        tools;
@@ -382,11 +389,15 @@ struct autoparser {
 
     autoparser() = default;
 
+    // Find the starting marker for the user message and assistant message
+    std::string detect_user_start_marker(const common_chat_template & tmpl);
+    std::string detect_assistant_start_marker(const common_chat_template & tmpl);
+
     // Run full differential analysis on a template
     void analyze_template(const common_chat_template & tmpl);
 
     // Build the PEG parser for this template
-    common_peg_arena build_parser(const generation_params & inputs) const;
+    common_peg_arena build_parser(const generation_params & inputs, const std::string & generation_prompt) const;
 
   private:
     // Collect tokens from entire analysis to preserve

common/chat-diff-analyzer.cpp

@@ -8,6 +8,9 @@
 #include "peg-parser.h"
 
 #include <algorithm>
+#include <cctype>
+#include <ostream>
+#include <sstream>
 
 #define ANSI_RESET  "\033[0m"
 #define ANSI_PURPLE "\033[1m\x1b[38;5;126m"
@@ -23,6 +26,7 @@ static const std::string FUN_SECOND = "SSS_SECOND_FUN_S";
 static const std::string ARG_FIRST = "AA_ARG_FST_AA";
 static const std::string ARG_SECOND = "BB_ARG_SND_BB";
 static const std::string USER_MSG = "U_USER_MSG Hello END_U";
+static const std::string USER_MSG_TWO = "V_USER_MSG Hello END_V";
 static const std::string ASSISTANT_MSG = "A_ASST_MSG I can help END_A";
 static const std::string THINKING_CONTENT = "REASON_PART I am thinking END_R";
 static const std::string CALL_ID_001 = "call00001";
@@ -71,6 +75,7 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
               analysis.content.end   = "<|END_OF_TURN_TOKEN|>";
               analysis.preserved_tokens.push_back("<|CHATBOT_TOKEN|>");
               analysis.preserved_tokens.push_back("<|END_OF_TURN_TOKEN|>");
+              analysis.user_start = "<|START_OF_TURN_TOKEN|><|USER_TOKEN|>";
               LOG_DBG(ANSI_ORANGE "[Patch: Cohere Command R+]\n" ANSI_RESET);
           }
       },
@@ -108,7 +113,59 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
               analysis.tools.function.close        = "```";
               LOG_DBG(ANSI_ORANGE "[Patch: DeepSeek-R1-Distill-Qwen]\n" ANSI_RESET);
           }
-      }
+      },
+      // Nemotron Nano v2
+      [](const common_chat_template & tmpl, autoparser & analysis) -> void {
+          if (tmpl.src.find("<SPECIAL_10>") != std::string::npos && tmpl.src.find("<SPECIAL_11>") != std::string::npos &&
+              tmpl.src.find("<SPECIAL_12>") != std::string::npos && tmpl.src.find("<TOOL_RESPONSE>") != std::string::npos) {
+
+              analysis.tools.format.mode           = tool_format::JSON_NATIVE;
+              analysis.tools.format.section_start  = "";
+              analysis.tools.format.section_end    = "";
+              analysis.tools.format.per_call_start = "<TOOLCALL>";
+              analysis.tools.format.per_call_end   = "</TOOLCALL>";
+              analysis.content.mode                = content_mode::PLAIN;
+              analysis.content.start               = "";
+              analysis.content.end                 = "";
+              analysis.reasoning.mode              = reasoning_mode::TAG_BASED;
+              analysis.reasoning.start             = "<think>\n\n";
+              analysis.reasoning.end               = "</think>";
+              analysis.assistant_start             = "<SPECIAL_11>Assistant";
+              analysis.user_start                  = "<SPECIAL_11>User";
+              analysis.preserved_tokens.clear();
+              analysis.preserved_tokens.push_back("<SPECIAL_12>");
+              analysis.preserved_tokens.push_back("<SPECIAL_11>");
+              analysis.preserved_tokens.push_back("</think>");
+              analysis.preserved_tokens.push_back("<TOOLCALL>");
+              analysis.preserved_tokens.push_back("</TOOLCALL>");
+              LOG_DBG(ANSI_ORANGE "[Patch: Nemotron Nano v2]\n" ANSI_RESET);
+          }
+      },
+      // Fireworks
+      [](const common_chat_template & tmpl, autoparser & analysis) -> void {
+          if (tmpl.src.find("{%- set system_prompt = '<|start_header_id|>' + 'system' + '<|end_header_id|>\\n\\n'"
+            " + message['content'] | trim + '\\n' + system_prompt_suffix + '<|eot_id|>' -%}") != std::string::npos) {
+              analysis.assistant_start             = "<|start_header_id|>assistant<|end_header_id|>";
+              analysis.user_start                  = "<|start_header_id|>user<|end_header_id|>";
+              LOG_DBG(ANSI_ORANGE "[Patch: Fireworks v2]\n" ANSI_RESET);
+          }
+      },
+      // Solar Open
+      [](const common_chat_template & tmpl, autoparser & analysis) -> void {
+          if (tmpl.src.find("<|begin|>assistant<|think|><|end|>") != std::string::npos) {
+              analysis.assistant_start             = "<|begin|>assistant";
+              LOG_DBG(ANSI_ORANGE "[Patch: Solar Open]\n" ANSI_RESET);
+          }
+      },
+      // Apriel 1.6
+      [](const common_chat_template & tmpl, autoparser & analysis) -> void {
+          if (tmpl.src.find("if not loop.last and '[BEGIN FINAL RESPONSE]' in asst_text") != std::string::npos) {
+              analysis.user_start                  = "<|begin_user|>";
+              analysis.assistant_start             = "<|begin_assistant|>";
+              LOG_DBG(ANSI_ORANGE "[Patch: Apriel 1.6]\n" ANSI_RESET);
+          }
+      },
+
     });
 
 // Common JSON structures
@@ -166,6 +223,8 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
     reasoning = analyze_reasoning(tmpl, jinja_caps.supports_tool_calls);
     content = analyze_content(tmpl, reasoning);
     tools = analyze_tools(jinja_caps.supports_tool_calls ? analyze_tools(tmpl, jinja_caps, reasoning) : analyze_tools());
+    assistant_start = detect_assistant_start_marker(tmpl);
+    user_start = detect_user_start_marker(tmpl);
     collect_preserved_tokens();
 
     for (auto & workaround : workarounds) {
@@ -173,6 +232,8 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
     }
 
     LOG_DBG("\n--- Reasoning & Content Structure ---\n");
+    LOG_DBG("user_msg_start: %s\n", user_start.c_str());
+    LOG_DBG("assistant_msg_start: %s\n", assistant_start.c_str());
     LOG_DBG("reasoning_mode: %s\n", mode_to_str(reasoning.mode).c_str());
     LOG_DBG("reasoning_start: '%s'\n", reasoning.start.c_str());
     LOG_DBG("reasoning_end: '%s'\n", reasoning.end.c_str());
@@ -245,6 +306,120 @@ void autoparser::collect_preserved_tokens() {
     add_token(tools.call_id.suffix);
 }
 
+std::string autoparser::detect_assistant_start_marker(const common_chat_template & tmpl) {
+    json user_msg = json{
+        { "role",    "user"   },
+        { "content", USER_MSG }
+    };
+
+    json assistant_no_reasoning = json{
+        { "role",    "assistant"   },
+        { "content", ASSISTANT_MSG }
+    };
+
+    template_params params;
+    params.messages              = json::array({ user_msg });
+    params.add_generation_prompt = false;
+    params.enable_thinking       = true;
+
+    auto comparison = compare_variants(
+        tmpl, params, [&](template_params & p) {
+            p.messages = json::array({ user_msg, assistant_no_reasoning });
+        }
+    );
+
+    if (!comparison) {
+        LOG_DBG(ANSI_ORANGE "%s: Template application failed, skipping assistant start detection\n" ANSI_RESET, __func__);
+        return "";
+    }
+
+    auto usermsg = comparison->diff.right;
+    if (usermsg.find(ASSISTANT_MSG) == std::string::npos) {
+        LOG_DBG(ANSI_ORANGE "%s: Did not find assistant message in assistant message block, skipping detection\n" ANSI_RESET, __func__);
+    }
+
+    auto ast_prefix = usermsg.substr(0, usermsg.find(ASSISTANT_MSG));
+    if (!reasoning.start.empty() && ast_prefix.find(trim_whitespace(reasoning.start)) != std::string::npos) {
+        ast_prefix = ast_prefix.substr(0, ast_prefix.find(trim_whitespace(reasoning.start)));
+    }
+    if (!reasoning.end.empty() && ast_prefix.find(trim_whitespace(reasoning.end)) != std::string::npos) {
+        ast_prefix = ast_prefix.substr(0, ast_prefix.find(trim_whitespace(reasoning.end)));
+    }
+    return trim_whitespace(ast_prefix);
+}
+
+std::string autoparser::detect_user_start_marker(const common_chat_template & tmpl) {
+    json user_msg = json{
+        { "role",    "user"   },
+        { "content", USER_MSG }
+    };
+
+    json assistant = json{
+        { "role",    "assistant"   },
+        { "content", ASSISTANT_MSG }
+    };
+
+    json user_msg_two = json{
+        { "role",    "user"       },
+        { "content", USER_MSG_TWO }
+    };
+
+    template_params params;
+    params.messages              = json::array({});
+    params.add_generation_prompt = false;
+    params.enable_thinking       = true;
+
+    auto comparison = compare_variants(
+        tmpl, params, [&](template_params & p) {
+            p.messages = json::array({ user_msg });
+        }
+    );
+
+    if (!comparison) {
+        LOG_DBG(ANSI_ORANGE "%s: Template application failed, unsupported empty messages? trying complex variant\n" ANSI_RESET, __func__);
+        params.messages = json::array({ user_msg_two, assistant });
+        comparison = compare_variants(
+            tmpl, params, [&](template_params & p) {
+                p.messages = json::array({ user_msg_two, assistant, user_msg });
+            }
+        );
+        if (!comparison) {
+            LOG_DBG(ANSI_ORANGE "%s: Template application failed for reserve variant, aborting\n" ANSI_RESET, __func__);
+            return "";
+        }
+    }
+
+    auto usermsg = comparison->diff.right;
+    if (usermsg.find(USER_MSG) == std::string::npos) {
+        LOG_DBG(ANSI_ORANGE "%s: Did not find user message in user message block, aborting detection\n" ANSI_RESET, __func__);
+    }
+
+    if (usermsg.find(ASSISTANT_MSG) != std::string::npos) {
+        usermsg = usermsg.substr(usermsg.find(ASSISTANT_MSG) + ASSISTANT_MSG.size());
+    }
+
+    auto candidate = usermsg.substr(0, usermsg.find(USER_MSG));
+    auto candidate_split = segmentize_markers(candidate);
+    std::stringstream result;
+    bool encountered_marker = false;
+    for (const auto & mrk : candidate_split) {
+        std::string lower_mrk = std::string(mrk.value);
+        std::transform(lower_mrk.begin(), lower_mrk.end(), lower_mrk.begin(),
+            [](unsigned char c) { return std::tolower(c); });
+        // heuristic to weed out potential end markers, but only at the start
+        if (mrk.type == segment_type::MARKER && !encountered_marker &&
+            (lower_mrk.find("end") != std::string::npos || lower_mrk.find("close") != std::string::npos)) {
+            continue;
+        }
+        if (mrk.type == segment_type::TEXT && !encountered_marker && trim_whitespace(mrk.value).empty()) {
+            continue;
+        }
+        encountered_marker |= mrk.type == segment_type::MARKER;
+        result << mrk.value;
+    }
+    return trim_whitespace(result.str());
+}
+
 analyze_reasoning::analyze_reasoning(const common_chat_template & tmpl, bool supports_tools)
     : analyze_base(tmpl) {
     LOG_DBG(ANSI_PURPLE "=== Starting differential analysis ===\n" ANSI_RESET);
@@ -342,7 +517,7 @@ void analyze_reasoning::compare_thinking_enabled() {
     if (left_trimmed.empty() && !diff.right.empty()) {
         if (!right_trimmed.empty() && string_ends_with(comparison->output_B, right_trimmed)) {
             if (start.empty()) {
-                start = trim_leading_whitespace(diff.right);
+                start = diff.right;
                 mode  = reasoning_mode::TAG_BASED;
             }
         }
@@ -353,7 +528,7 @@ void analyze_reasoning::compare_thinking_enabled() {
                 if (seg.size() >= 2 && seg[seg.size() - 1].value == left_trimmed && seg[seg.size() - 2].type == segment_type::MARKER) {
                     start = seg[seg.size() - 2].value;
                 }
-                end = trim_trailing_whitespace(diff.left);
+                end = diff.left;
                 mode = reasoning_mode::TAG_BASED;
             }
         }
@@ -445,14 +620,14 @@ void analyze_reasoning::compare_reasoning_scope() {
         auto result = parser_wrapped.parse_anywhere_and_extract(comparison->output_B);
         if (result.result.success()) {
             start = result.tags["pre"];
-            end = trim_trailing_whitespace(result.tags["post"]);
+            end = result.tags["post"];
         } else {
             auto parser_delimiter = build_tagged_peg_parser([&](common_peg_parser_builder &p) {
                 return p.literal(reasoning_content) + p.space() + p.optional(p.tag("post", (p.marker() + p.space())));
             });
             result = parser_delimiter.parse_anywhere_and_extract(comparison->output_B);
             if (result.result.success()) {
-                end = trim_trailing_whitespace(result.tags["post"]);
+                end = result.tags["post"];
             } else {
                 LOG_DBG(ANSI_ORANGE "%s: Unable to extract reasoning markers, falling back to reasoning = NONE\n" ANSI_RESET, __func__);
                 mode = reasoning_mode::NONE;

common/chat-peg-parser.cpp

@@ -358,35 +358,7 @@ void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
             if (is_potential_container) {
                 value_content = normalize_container_value(value_content);
             }
-
-            // Try to parse as JSON value (number, bool, null, object, array)
-            try {
-                ordered_json parsed = ordered_json::parse(value_content);
-                if (parsed.is_string()) {
-                    // Don't add closing quote yet (added by arg_close) for monotonic streaming
-                    std::string escaped = parsed.dump();
-                    if (!escaped.empty() && escaped.back() == '"') {
-                        escaped.pop_back();
-                    }
-                    value_to_add          = escaped;
-                    closing_quote_pending = true;
-                } else {
-                    // Non-string values: use raw content to preserve whitespace for monotonicity
-                    value_to_add = value_content;
-                }
-            } catch (...) {
-                if (node.is_partial && is_potential_container) {
-                    // Partial container: pass through the already-normalized content
-                    value_to_add = value_content;
-                } else {
-                    // Not valid JSON - treat as string value
-                    if (!closing_quote_pending) {
-                        value_to_add          = "\"";
-                        closing_quote_pending = true;
-                    }
-                    value_to_add += escape_json_string_inner(value_content);
-                }
-            }
+            value_to_add += value_content;
         }
 
         args_target() += value_to_add;
@@ -813,7 +785,33 @@ common_peg_parser common_chat_peg_builder::prefix(const std::string & s, const s
     if (delimiter.empty()) {
         return literal(s);
     }
-    return literal(s.substr(0, s.rfind(delimiter)));
+    return literal(s.substr(0, s.find(delimiter)));
+}
+
+common_peg_parser common_chat_peg_builder::optspace(const std::string & tag) {
+    auto parser = eps();
+    size_t end_of_prefix_space = tag.size();
+    size_t start_of_suffix_space = tag.size();
+    for (size_t i = 0; i < tag.size(); i++) {
+        if (!std::isspace(tag[i])) {
+            end_of_prefix_space = i;
+            break;
+        }
+    }
+    for (size_t i = tag.size(); i > 0; i--) {
+        if (!std::isspace(tag[i - 1])) {
+            start_of_suffix_space = i;
+            break;
+        }
+    }
+    for (size_t i = 0; i < end_of_prefix_space; i++) {
+        parser += optional(literal(std::string(1, tag[i])));
+    }
+    parser += literal(tag.substr(end_of_prefix_space, start_of_suffix_space - end_of_prefix_space));
+    for (size_t i = start_of_suffix_space; i < tag.size(); i++) {
+        parser += optional(literal(std::string(1, tag[i])));
+    }
+    return parser;
 }
 
 common_peg_parser common_chat_peg_builder::standard_json_tools(

common/chat-peg-parser.h

@@ -90,12 +90,15 @@ class common_chat_peg_builder : public common_peg_parser_builder {
 
     // Use for schema-declared string types - won't be treated as potential JSON container
     common_peg_parser tool_arg_string_value(const common_peg_parser & p) { return tag(TOOL_ARG_STRING_VALUE, p); }
-    common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_VALUE, p)); }
+    common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return tag(TOOL_ARG_VALUE, p); }
 
 
     // Return a parser that parses the prefix of a string, up to a given delimiter.
     common_peg_parser prefix(const std::string & s, const std::string & delimiter = {});
 
+    // Return a parser that parses all elements of tag, but leading and trailing spaces are optional
+    common_peg_parser optspace(const std::string & tag);
+
     // Legacy-compatible helper for building standard JSON tool calls
     // Used by tests and manual parsers
     // name_key/args_key: JSON key names for function name and arguments

common/chat.cpp

@@ -70,6 +70,65 @@ static bool has_content_or_tool_calls(const common_chat_msg & msg) {
     return !msg.content.empty() || !msg.tool_calls.empty();
 }
 
+std::string common_chat_msg::render_content(const std::string & delimiter) const {
+    if (!content.empty() && !content_parts.empty()) {
+        throw std::runtime_error("Cannot specify both content and content_parts");
+    }
+    if (!content.empty()) {
+        return content;
+    }
+
+    std::string text;
+    for (const auto & part : content_parts) {
+        if (part.type == "text") {
+            if (!text.empty()) {
+                text += delimiter;
+            }
+            text += part.text;
+        }
+    }
+    return text;
+}
+
+std::vector<common_chat_msg_span> common_chat_split_by_role(const std::string & prompt, const std::vector<common_chat_msg_delimiter> & delims) {
+    if (delims.empty() || prompt.empty()) {
+        return {};
+    }
+
+    auto parser = build_peg_parser([&](common_peg_parser_builder & p) {
+        std::vector<std::string>       all_delims;
+        std::vector<common_peg_parser> tagged_messages;
+
+        all_delims.reserve(delims.size());
+        tagged_messages.reserve(delims.size());
+        for (const auto & d : delims) {
+            all_delims.push_back(d.delimiter);
+        }
+
+        auto any_delim = p.until_one_of(all_delims);
+        for (const auto & d : delims) {
+            tagged_messages.push_back(p.tag(d.role, p.literal(d.delimiter) + any_delim));
+        }
+
+        return any_delim + p.zero_or_more(p.choice(tagged_messages)) + p.end();
+    });
+
+    common_peg_parse_context ctx(prompt);
+    const auto result = parser.parse(ctx);
+    if (!result.success()) {
+        return {};
+    }
+
+    std::vector<common_chat_msg_span> spans;
+    ctx.ast.visit(result, [&](const common_peg_ast_node & node) {
+        if (!node.tag.empty()) {
+            spans.push_back({ node.tag, node.start, node.end - node.start });
+        }
+    });
+
+    return spans;
+}
+
 json common_chat_msg::to_json_oaicompat(bool concat_typed_text) const {
     if (!content.empty() && !content_parts.empty()) {
         throw std::runtime_error("Cannot specify both content and content_parts");
@@ -80,7 +139,7 @@ json common_chat_msg::to_json_oaicompat(bool concat_typed_text) const {
     if (!content.empty()) {
         jmsg["content"] = content;
     } else if (!content_parts.empty()) {
-        if (concat_typed_text) {
+        if (concat_typed_text || contains_media()) {
             std::string text;
             bool last_was_media_marker = false;
             // join parts with newline, do not add newline before or after media markers
@@ -451,6 +510,22 @@ std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const json & too
     return result;
 }
 
+common_chat_continuation common_chat_continuation_parse(const nlohmann::ordered_json & value) {
+    if (value.is_boolean() && value.get<bool>()) {
+        return COMMON_CHAT_CONTINUATION_AUTO;
+    }
+    if (value.is_string()) {
+        auto value_str = value.get<std::string>();
+        if (value_str == "reasoning_content") {
+            return COMMON_CHAT_CONTINUATION_REASONING;
+        }
+        if (value_str == "content") {
+            return COMMON_CHAT_CONTINUATION_CONTENT;
+        }
+    }
+    return COMMON_CHAT_CONTINUATION_NONE;
+}
+
 bool common_chat_verify_template(const std::string & tmpl, bool use_jinja) {
     if (use_jinja) {
         try {
@@ -811,6 +886,36 @@ std::string common_chat_template_direct_apply(
     return common_chat_template_direct_apply_impl(tmpl, inputs, std::nullopt, std::nullopt, std::nullopt);
 }
 
+static std::string common_chat_template_generation_prompt_impl(
+    const common_chat_template & tmpl,
+    const autoparser::generation_params & inputs,
+    const std::optional<json> & messages_override = std::nullopt,
+    const std::optional<json> & tools_override = std::nullopt,
+    const std::optional<json> & additional_context = std::nullopt) {
+
+    auto adjusted_messages = messages_override ? *messages_override : inputs.messages;
+
+    autoparser::generation_params params = inputs;
+    params.add_generation_prompt = false;
+    params.continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
+    std::string no_gen_prompt    = common_chat_template_direct_apply_impl(tmpl, params, adjusted_messages, tools_override, additional_context);
+    params.add_generation_prompt = true;
+    std::string gen_prompt       = common_chat_template_direct_apply_impl(tmpl, params, adjusted_messages, tools_override, additional_context);
+
+    size_t prefix_len = 0;
+    size_t min_size = std::min(no_gen_prompt.size(), gen_prompt.size());
+    while (prefix_len < min_size && no_gen_prompt[prefix_len] == gen_prompt[prefix_len]) {
+        prefix_len++;
+    }
+    return gen_prompt.substr(prefix_len);
+}
+
+std::string common_chat_template_generation_prompt(
+    const common_chat_template & tmpl,
+    const autoparser::generation_params & inputs) {
+    return common_chat_template_generation_prompt_impl(tmpl, inputs, std::nullopt, std::nullopt, std::nullopt);
+}
+
 static common_chat_params common_chat_params_init_ministral_3(const common_chat_template &    tmpl,
                                                               const autoparser::generation_params & inputs) {
     common_chat_params data;
@@ -863,6 +968,7 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
     data.thinking_start_tag = "[THINK]";
     data.thinking_end_tag   = "[/THINK]";
     data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
     data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
     data.preserved_tokens  = {
         "[THINK]",
@@ -871,8 +977,19 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
         "[ARGS]",
     };
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = "[THINK]" + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += "[/THINK]" + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
-        auto generation_prompt = p.prefix(inputs.generation_prompt, "[THINK]");
+        auto generation_prompt = p.eps();
         auto reasoning =
             extract_reasoning ? p.optional("[THINK]" + p.reasoning(p.until("[/THINK]")) + "[/THINK]") : p.eps();
 
@@ -963,6 +1080,15 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
     }
 
     data.prompt            = prompt;
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override= */ adjusted_messages);
+    data.message_spans = common_chat_split_by_role(prompt, {
+        { "assistant", "<|start|>assistant" },
+        { "user",      "<|start|>user"      },
+        { "system",    "<|start|>developer" },
+        { "system",    "<|start|>system"    },
+        { "tool",      "<|start|>functions" },
+    });
+
     data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
     data.supports_thinking = true;
 
@@ -972,6 +1098,18 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
         "<|channel|>", "<|constrain|>", "<|message|>", "<|start|>", "<|end|>",
     };
 
+    // Adjust prompt for continuation
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = "<|start|>assistant<|channel|>analysis<|message|>" + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += "<|end|><|start|>assistant<|channel|>final<|message|>" + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto has_tools           = inputs.tools.is_array() && !inputs.tools.empty();
     auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
     auto include_grammar     = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
@@ -1080,14 +1218,21 @@ static common_chat_params common_chat_params_init_gemma4(const common_chat_templ
     common_chat_params data;
 
     data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
 
     if (inputs.add_generation_prompt && string_ends_with(data.prompt, "<turn|>\n")) {
         // This may happen if the model generates content + tool_call, the
         // template does not add the model's next turn and confuses the model
         // from emitting its proper reasoning token sequence.
-        data.prompt += "<|turn>model\n";
+        data.generation_prompt = "<|turn>model\n";
+        data.prompt += data.generation_prompt;
     }
 
+    data.message_spans = common_chat_split_by_role(data.prompt, {
+        { "user",      "<|turn>user\n"  },
+        { "assistant", "<|turn>model\n" },
+    });
+
     data.format            = COMMON_CHAT_FORMAT_PEG_GEMMA4;
     data.supports_thinking  = true;
     data.thinking_start_tag = "<|channel>thought";
@@ -1101,13 +1246,25 @@ static common_chat_params common_chat_params_init_gemma4(const common_chat_templ
         "<|turn>",
     };
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = string_ends_with(data.prompt, "<turn|>\n") ? "<|turn>model\n" : "";
+        data.generation_prompt += "<|channel>thought\n" + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += "<channel|>" + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto has_tools           = inputs.tools.is_array() && !inputs.tools.empty();
     auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
     auto include_grammar     = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
     auto extract_reasoning   = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
 
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
-        auto start = p.rule("start", p.prefix(inputs.generation_prompt, "<|channel>"));
+        auto start = p.rule("start", p.optional(p.literal("<|turn>model\n")));
 
         if (extract_reasoning) {
             p.rule("thought", p.literal("<|channel>thought") + p.space() + p.reasoning(p.until("<channel|>")) + p.literal("<channel|>"));
@@ -1224,15 +1381,22 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_
                                                                    const autoparser::generation_params & inputs) {
     common_chat_params data;
 
-    data.prompt           = common_chat_template_direct_apply_impl(tmpl, inputs);
-    data.format           = COMMON_CHAT_FORMAT_PEG_NATIVE;
-    data.preserved_tokens = {
+    data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
+    data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.preserved_tokens  = {
         ">>>all",
     };
 
     auto has_tools         = inputs.tools.is_array() && !inputs.tools.empty();
     auto include_grammar   = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+        data.generation_prompt = "<|start_header_id|>assistant<|end_header_id|>\n\n>>>all\n" + msg.render_content();
+        data.prompt += data.generation_prompt;
+    }
+
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
         // Functionary v3.2 format:
         // - Normal content: >>>all\n{content}
@@ -1244,7 +1408,7 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_
         // When no tools, content goes until end
         auto content_until_tool = p.literal("all\n") + p.content(p.until(">>>"));
         auto content_until_end  = p.literal("all\n") + p.content(p.rest());
-        auto generation_prompt  = p.literal(inputs.generation_prompt);
+        auto generation_prompt  = p.literal("<|start_header_id|>assistant<|end_header_id|>\n\n>>>");
 
         // If no tools or tool_choice is NONE, just parse content
         if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
@@ -1318,9 +1482,10 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
                                                           const autoparser::generation_params & inputs) {
     common_chat_params data;
 
-    data.prompt             = common_chat_template_direct_apply_impl(tmpl, inputs);
-    data.format             = COMMON_CHAT_FORMAT_PEG_NATIVE;
-    data.supports_thinking  = true;
+    data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
+    data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.supports_thinking = true;
     data.preserved_tokens  = {
         "<|tool_calls_section_begin|>",
         "<|tool_calls_section_end|>",
@@ -1343,10 +1508,22 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
 
     const std::string THINK_START = "<think>";
     const std::string THINK_END   = "</think>";
+    const std::string GEN_PROMPT  = "<|im_assistant|>assistant<|im_middle|>";
 
     data.thinking_start_tag = THINK_START;
     data.thinking_end_tag   = THINK_END;
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += THINK_END + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
         // Kimi K2 Thinking format:
         // - Reasoning: <think>{reasoning}</think>
@@ -1366,7 +1543,7 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
         auto reasoning = extract_reasoning ? p.optional(THINK_START + p.reasoning(
             p.until_one_of({ THINK_END, "<|tool_calls_section_begin|>", "<|tool_call_begin|>" })) +
             p.optional(p.literal(THINK_END))) : p.eps();
-        auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
+        auto generation_prompt = p.literal(GEN_PROMPT);
 
 
         // Content only parser (no tools)
@@ -1442,6 +1619,7 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
     common_chat_params data;
 
     data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
     data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
     data.supports_thinking = true;
     data.preserved_tokens  = {
@@ -1461,12 +1639,24 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
     const std::string TOOL_CALL_END   = "<|tool_call_end|>";
     const std::string THINK_START     = "<think>";
     const std::string THINK_END       = "</think>";
+    const std::string GEN_PROMPT      = "<|im_start|>assistant\n";
 
     data.thinking_start_tag = THINK_START;
     data.thinking_end_tag   = THINK_END;
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += THINK_END + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
-        auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
+        auto generation_prompt = p.literal(GEN_PROMPT);
         auto end = p.end();
 
         auto reasoning = p.eps();
@@ -1521,6 +1711,7 @@ static common_chat_params common_chat_params_init_lfm2_5(const common_chat_templ
     common_chat_params data;
 
     data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
     data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
     data.supports_thinking = true;
     data.preserved_tokens  = {
@@ -1536,12 +1727,24 @@ static common_chat_params common_chat_params_init_lfm2_5(const common_chat_templ
 
     const std::string THINK_START     = "<think>";
     const std::string THINK_END       = "</think>";
+    const std::string GEN_PROMPT      = "<|im_start|>assistant\n";
 
     data.thinking_start_tag = THINK_START;
     data.thinking_end_tag   = THINK_END;
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += THINK_END + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
+
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
-        auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
+        auto generation_prompt = p.literal(GEN_PROMPT);
         auto end = p.end();
 
         auto reasoning = p.eps();
@@ -1592,6 +1795,7 @@ static common_chat_params common_chat_params_init_gigachat_v3(
     common_chat_params data;
 
     data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
     data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
     data.supports_thinking = false;
     data.preserved_tokens  = {
@@ -1599,6 +1803,12 @@ static common_chat_params common_chat_params_init_gigachat_v3(
         "<|role_sep|>\n",
     };
 
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+        data.generation_prompt = "assistant<|role_sep|>\n" + msg.render_content();
+        data.prompt += data.generation_prompt;
+    }
+
     auto has_tools         = inputs.tools.is_array() && !inputs.tools.empty();
     auto include_grammar   = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
     const auto *tool_call_start_prefix = "<|message_sep|>\n\nfunction call<|role_sep|>\n";
@@ -1634,7 +1844,7 @@ static common_chat_params common_chat_params_init_gigachat_v3(
             ret = p.content(p.rest());
         }
 
-        return p.literal(inputs.generation_prompt) + ret;
+        return p.literal("assistant<|role_sep|>\n") + ret;
     });
 
     data.parser = parser.save();
@@ -1662,12 +1872,13 @@ static common_chat_params common_chat_params_init_deepseek_v3_2(const common_cha
                                                                  const autoparser::generation_params & inputs) {
     common_chat_params data;
 
-    data.prompt            = common_chat_template_direct_apply_impl(tmpl, inputs);
-    data.format            = COMMON_CHAT_FORMAT_PEG_NATIVE;
-    data.supports_thinking = true;
+    data.prompt             = common_chat_template_direct_apply_impl(tmpl, inputs);
+    data.generation_prompt  = common_chat_template_generation_prompt_impl(tmpl, inputs);
+    data.format             = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.supports_thinking  = true;
     data.thinking_start_tag = "<think>";
     data.thinking_end_tag   = "</think>";
-    data.preserved_tokens  = {
+    data.preserved_tokens   = {
         "｜DSML｜",
         "<think>",
         "</think>",
@@ -1687,9 +1898,21 @@ static common_chat_params common_chat_params_init_deepseek_v3_2(const common_cha
     const std::string INVOKE_END   = "</" + DSML + "invoke>";
     const std::string PARAM_START  = "<" + DSML + "parameter";
     const std::string PARAM_END    = "</" + DSML + "parameter>";
+    const std::string GEN_PROMPT   = "<｜Assistant｜>";
+
+    if (inputs.has_continuation()) {
+        const auto & msg = inputs.continue_msg;
+
+        data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
+        if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
+            data.generation_prompt += THINK_END + msg.render_content();
+        }
+
+        data.prompt += data.generation_prompt;
+    }
 
     auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
-        auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
+        auto generation_prompt = p.literal(GEN_PROMPT);
         auto end = p.end();
 
         auto reasoning = p.eps();
@@ -2122,16 +2345,38 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
     params.tools = common_chat_tools_to_json_oaicompat(inputs.tools);
     const auto & tmpl =
         params.tools.is_array() && tmpls->template_tool_use ? *tmpls->template_tool_use : *tmpls->template_default;
-    const auto & src        = tmpl.source();
-    const auto & caps       = tmpl.original_caps();
-    params.messages         = render_message_to_json(inputs.messages, tmpl.original_caps());
-    params.tool_choice      = inputs.tool_choice;
-    params.reasoning_format = inputs.reasoning_format;
-    params.enable_thinking  = inputs.enable_thinking;
-    params.grammar          = inputs.grammar;
-    params.now              = inputs.now;
-    params.add_bos          = tmpls->add_bos;
-    params.add_eos          = tmpls->add_eos;
+    const auto & src             = tmpl.source();
+    const auto & caps            = tmpl.original_caps();
+    params.messages              = render_message_to_json(inputs.messages, tmpl.original_caps());
+    params.tool_choice           = inputs.tool_choice;
+    params.reasoning_format      = inputs.reasoning_format;
+    params.enable_thinking       = inputs.enable_thinking;
+    params.grammar               = inputs.grammar;
+    params.now                   = inputs.now;
+    params.add_generation_prompt = inputs.add_generation_prompt;
+    params.add_bos               = tmpls->add_bos;
+    params.add_eos               = tmpls->add_eos;
+
+    params.continue_final_message = inputs.continue_final_message;
+    if (params.continue_final_message != COMMON_CHAT_CONTINUATION_NONE) {
+        params.add_generation_prompt = false;
+
+        if (!inputs.messages.empty()) {
+            // Render messages[:-1] and store continuation message separately
+            params.continue_msg = inputs.messages.back();
+            params.messages.erase(params.messages.size() - 1);
+        }
+
+        if (params.continue_final_message == COMMON_CHAT_CONTINUATION_AUTO && !inputs.messages.empty()) {
+            // Resolve based on message content
+            params.continue_final_message = COMMON_CHAT_CONTINUATION_CONTENT;
+            if (!params.continue_msg.reasoning_content.empty() &&
+                params.continue_msg.content.empty() &&
+                params.continue_msg.content_parts.empty()) {
+                params.continue_final_message = COMMON_CHAT_CONTINUATION_REASONING;
+            }
+        }
+    }
 
     if (src.find("<|channel|>") == std::string::npos) {
         // map developer to system for all models except for GPT-OSS
@@ -2153,15 +2398,6 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
         workaround::func_args_not_string(params.messages);
     }
 
-    params.add_generation_prompt = false;
-    std::string no_gen_prompt    = common_chat_template_direct_apply_impl(tmpl, params);
-    params.add_generation_prompt = true;
-    std::string gen_prompt       = common_chat_template_direct_apply_impl(tmpl, params);
-    auto        diff             = calculate_diff_split(no_gen_prompt, gen_prompt);
-    params.generation_prompt     = diff.right + diff.suffix;
-
-    params.add_generation_prompt = inputs.add_generation_prompt;
-
     params.extra_context = common_chat_extra_context();
     for (auto el : inputs.chat_template_kwargs) {
         params.extra_context[el.first] = json::parse(el.second);
@@ -2191,17 +2427,16 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
         auto params_copy               = params;
         params_copy.reasoning_format   = COMMON_REASONING_FORMAT_NONE;
         data.prompt                    = common_chat_template_direct_apply_impl(tmpl, params_copy);
+        data.generation_prompt         = common_chat_template_generation_prompt_impl(tmpl, params);
         data.format                    = COMMON_CHAT_FORMAT_PEG_NATIVE;
-        data.generation_prompt         = params.generation_prompt;
-        auto parser                    = build_chat_peg_parser([&params](common_chat_peg_builder &p) {
-            return p.prefix(params.generation_prompt) << p.content(p.rest());
+        auto parser                    = build_chat_peg_parser([&data](common_chat_peg_builder &p) {
+            return p.literal(data.generation_prompt) << p.content(p.rest());
         });
         data.parser                    = parser.save();
         return data;
     }
 
     if (auto result = common_chat_try_specialized_template(tmpl, src, params)) {
-        result->generation_prompt = params.generation_prompt;
         return *result;
     }
 
@@ -2210,12 +2445,24 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
         struct autoparser::autoparser autoparser;
         autoparser.analyze_template(tmpl);
         auto auto_params = autoparser::peg_generator::generate_parser(tmpl, params, autoparser);
+
+        std::vector<common_chat_msg_delimiter> delimiters;
+        if (!autoparser.assistant_start.empty()) {
+            delimiters.push_back({ "assistant", autoparser.assistant_start });
+        }
+        if (!autoparser.user_start.empty()) {
+            delimiters.push_back({ "user", autoparser.user_start });
+        }
+
+        if (!delimiters.empty()) {
+            auto_params.message_spans = common_chat_split_by_role(auto_params.prompt, delimiters);
+        }
+
         auto_params.supports_thinking = autoparser.reasoning.mode != autoparser::reasoning_mode::NONE;
         if (auto_params.supports_thinking) {
-            auto_params.thinking_start_tag = autoparser.reasoning.start;
-            auto_params.thinking_end_tag   = autoparser.reasoning.end;
+            auto_params.thinking_start_tag = trim_whitespace(autoparser.reasoning.start);
+            auto_params.thinking_end_tag   = trim_whitespace(autoparser.reasoning.end);
         }
-        auto_params.generation_prompt = params.generation_prompt;
         common_peg_arena arena;
         arena.load(auto_params.parser);
         LOG_DBG("%s: generated parser:\n%s\n\nparser generation prompt: %s\n", __func__, arena.dump(arena.root()).c_str(), auto_params.generation_prompt.c_str());

common/chat.h

@@ -89,11 +89,22 @@ struct common_chat_msg {
 
     nlohmann::ordered_json to_json_oaicompat(bool concat_typed_text = false) const;
 
+    std::string render_content(const std::string & delimiter = "\n\n") const;
+
     bool empty() const {
         return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() &&
                tool_name.empty() && tool_call_id.empty();
     }
 
+    bool contains_media() const {
+        for (const auto & part : content_parts) {
+            if (part.type == "media_marker") {
+                return true;
+            }
+        }
+        return false;
+    }
+
     void set_tool_call_ids(std::vector<std::string> &           ids_cache,
                            const std::function<std::string()> & gen_tool_call_id) {
         for (auto i = 0u; i < tool_calls.size(); i++) {
@@ -132,6 +143,17 @@ struct common_chat_msg_diff {
     }
 };
 
+struct common_chat_msg_span {
+    std::string role;
+    std::size_t pos = 0;
+    std::size_t len = 0;
+};
+
+struct common_chat_msg_delimiter {
+    std::string role;
+    std::string delimiter;
+};
+
 struct common_chat_tool {
     std::string name;
     std::string description;
@@ -155,12 +177,22 @@ enum common_chat_format {
     COMMON_CHAT_FORMAT_COUNT,  // Not a format, just the # formats
 };
 
+
+// Continuation method provided via `continue_final_message`
+enum common_chat_continuation {
+    COMMON_CHAT_CONTINUATION_NONE,
+    COMMON_CHAT_CONTINUATION_AUTO,
+    COMMON_CHAT_CONTINUATION_REASONING,
+    COMMON_CHAT_CONTINUATION_CONTENT,
+};
+
 struct common_chat_templates_inputs {
     std::vector<common_chat_msg>          messages;
     std::string                           grammar;
     std::string                           json_schema;
-    bool                                  add_generation_prompt = true;
-    bool                                  use_jinja             = true;
+    bool                                  add_generation_prompt  = true;
+    common_chat_continuation              continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
+    bool                                  use_jinja              = true;
     // Parameters below only supported when use_jinja is true
     std::vector<common_chat_tool>         tools;
     common_chat_tool_choice               tool_choice         = COMMON_CHAT_TOOL_CHOICE_AUTO;
@@ -187,6 +219,7 @@ struct common_chat_params {
     std::vector<std::string>            preserved_tokens;
     std::vector<std::string>            additional_stops;
     std::string                         parser;
+    std::vector<common_chat_msg_span>   message_spans;
 };
 
 // per-message parsing syntax
@@ -198,6 +231,8 @@ struct common_chat_parser_params {
     bool                    reasoning_in_content = false;
     std::string             generation_prompt;
     bool                    parse_tool_calls     = true;
+    bool                    is_continuation      = false;
+    bool                    echo                 = false;  // Include assistant prefilled msg in output
     bool                    debug                = false;  // Enable debug output for PEG parser
     common_peg_arena        parser               = {};
     common_chat_parser_params() = default;
@@ -258,6 +293,8 @@ std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const nlohmann::or
 
 std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const nlohmann::ordered_json & tools);
 
+common_chat_continuation common_chat_continuation_parse(const nlohmann::ordered_json & value);
+
 // DEPRECATED: only used in tests
 nlohmann::ordered_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
 
@@ -270,11 +307,16 @@ std::string common_chat_template_direct_apply(
     const common_chat_template & tmpl,
     const autoparser::generation_params & inputs);
 
+std::string common_chat_template_generation_prompt(
+    const common_chat_template &          tmpl,
+    const autoparser::generation_params & inputs);
+
 std::optional<common_chat_params> common_chat_try_specialized_template(
         const common_chat_template &          tmpl,
         const std::string &                   src,
         autoparser::generation_params & params);
 
+
 // specialized per-task preset
 struct common_chat_prompt_preset {
     std::string system;
@@ -282,3 +324,6 @@ struct common_chat_prompt_preset {
 };
 
 common_chat_prompt_preset common_chat_get_asr_prompt(const common_chat_templates * chat_templates);
+
+std::vector<common_chat_msg_span> common_chat_split_by_role(const std::string & prompt, const std::vector<common_chat_msg_delimiter> & delims);
+

common/common.cpp

@@ -7,6 +7,7 @@
 #include "log.h"
 #include "llama.h"
 #include "sampling.h"
+#include "speculative.h"
 #include "unicode.h"
 
 #include <algorithm>
@@ -366,15 +367,33 @@ void common_init() {
     SetConsoleCP(CP_UTF8);
 #endif
 
-    llama_log_set(common_log_default_callback, NULL);
+    common_log_set_prefix(common_log_main(), true);
+    common_log_set_timestamps(common_log_main(), true);
 
+    llama_log_set(common_log_default_callback, NULL);
+}
+
+void common_params_print_info(const common_params & params, bool print_devices) {
 #ifdef NDEBUG
     const char * build_type = "";
 #else
     const char * build_type = " (debug)";
 #endif
+    LOG_TRC("%s: build %d (%s) with %s for %s%s\n", __func__, llama_build_number(), llama_commit(), llama_compiler(), llama_build_target(), build_type);
 
-    LOG_DBG("build: %d (%s) with %s for %s%s\n", llama_build_number(), llama_commit(), llama_compiler(), llama_build_target(), build_type);
+    LOG_INF("log_info: verbosity = %d (adjust with the `-lv N` CLI arg)\n", common_log_get_verbosity_thold());
+
+    // device enumeration creates a primary context on CUDA backends, skip it when the caller does not own any device
+    if (print_devices) {
+        LOG_INF("device_info:\n");
+        for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
+            auto * dev = ggml_backend_dev_get(i);
+            size_t free, total;
+            ggml_backend_dev_memory(dev, &free, &total);
+            LOG_INF("  - %-8s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024);
+        }
+    }
+    LOG_INF("%s\n", common_params_get_system_info(params).c_str());
 }
 
 std::string common_params_get_system_info(const common_params & params) {
@@ -426,6 +445,27 @@ std::string string_strip(const std::string & str) {
     return str.substr(start, end - start);
 }
 
+std::string string_lcs(std::string_view a, std::string_view b) {
+    if (a.empty() || b.empty()) return {};
+
+    std::vector<std::vector<size_t>> dp(a.size() + 1, std::vector<size_t>(b.size() + 1, 0));
+    size_t best_len = 0;
+    size_t best_end_a = 0;
+
+    for (size_t i = 1; i <= a.size(); ++i) {
+        for (size_t j = 1; j <= b.size(); ++j) {
+            if (a[i - 1] == b[j - 1]) {
+                dp[i][j] = dp[i - 1][j - 1] + 1;
+                if (dp[i][j] > best_len) {
+                    best_len = dp[i][j];
+                    best_end_a = i;
+                }
+            }
+        }
+    }
+    return std::string(a.substr(best_end_a - best_len, best_len));
+}
+
 std::string string_get_sortable_timestamp() {
     using clock = std::chrono::system_clock;
 
@@ -1141,19 +1181,20 @@ struct common_init_result::impl {
     std::vector<llama_sampler_seq_config> samplers_seq_config;
 };
 
-common_init_result::common_init_result(common_params & params) :
+common_init_result::common_init_result(common_params & params, bool model_only) :
     pimpl(new impl{}) {
     auto mparams = common_model_params_to_llama(params);
     auto cparams = common_context_params_to_llama(params);
 
     if (params.fit_params) {
-        LOG_INF("%s: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on\n", __func__);
+        LOG_INF("%s: fitting params to device memory ...\n", __func__);
+        LOG_INF("%s: (for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on)\n", __func__);
         common_fit_params(params.model.path.c_str(), &mparams, &cparams,
             params.tensor_split,
             params.tensor_buft_overrides.data(),
             params.fit_params_target.data(),
             params.fit_params_min_ctx,
-            params.verbosity >= 4 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
+            params.verbosity >= LOG_LEVEL_DEBUG ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
     }
 
     llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);
@@ -1163,6 +1204,10 @@ common_init_result::common_init_result(common_params & params) :
 
     pimpl->model.reset(model);
 
+    if (model_only) {
+        return;
+    }
+
     const llama_vocab * vocab = llama_model_get_vocab(model);
 
     // load and optionally apply lora adapters
@@ -1196,7 +1241,7 @@ common_init_result::common_init_result(common_params & params) :
     // initialize once
     for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
         if (llama_vocab_is_eog(vocab, i)) {
-            LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
+            LOG_TRC("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
             params.sampling.logit_bias_eog.push_back({i, -INFINITY});
         }
     }
@@ -1209,12 +1254,12 @@ common_init_result::common_init_result(common_params & params) :
     }
 
     //if (params.sampling.penalty_last_n == -1) {
-    //    LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
+    //    LOG_TRC("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
     //    params.sampling.penalty_last_n = llama_n_ctx(lctx);
     //}
 
     //if (params.sampling.dry_penalty_last_n == -1) {
-    //    LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
+    //    LOG_TRC("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
     //    params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
     //}
 
@@ -1266,8 +1311,8 @@ std::vector<llama_adapter_lora_ptr> & common_init_result::lora() {
     return pimpl->lora;
 }
 
-common_init_result_ptr common_init_from_params(common_params & params) {
-    common_init_result_ptr res(new common_init_result(params));
+common_init_result_ptr common_init_from_params(common_params & params, bool model_only) {
+    common_init_result_ptr res(new common_init_result(params, model_only));
 
     llama_model * model = res->model();
     if (model == NULL) {
@@ -1275,6 +1320,10 @@ common_init_result_ptr common_init_from_params(common_params & params) {
         return res;
     }
 
+    if (model_only) {
+        return res;
+    }
+
     llama_context * lctx = res->context();
     if (lctx == NULL) {
         LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
@@ -1338,7 +1387,7 @@ common_init_result_ptr common_init_from_params(common_params & params) {
     }
 
     if (params.warmup) {
-        LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
+        LOG_INF("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
 
         llama_set_warmup(lctx, true);
 
@@ -1420,9 +1469,15 @@ common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx) {
         goto done;
     }
 
+    if (llama_n_rs_seq(ctx) > 0) {
+        LOG_INF("%s: the context supports bounded partial sequence removal\n", __func__);
+        res = COMMON_CONTEXT_SEQ_RM_TYPE_RS;
+        goto done;
+    }
+
     // try to remove the last tokens
     if (!llama_memory_seq_rm(mem, 0, 1, -1)) {
-        LOG_WRN("%s: the target context does not support partial sequence removal\n", __func__);
+        LOG_TRC("%s: the context does not support partial sequence removal\n", __func__);
         res = COMMON_CONTEXT_SEQ_RM_TYPE_FULL;
         goto done;
     }
@@ -1434,6 +1489,23 @@ done:
     return res;
 }
 
+void common_context_seq_rm(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1) {
+    auto * mem = llama_get_memory(ctx);
+    if (!llama_memory_seq_rm(mem, seq_id, p0, p1)) {
+        GGML_ABORT("%s", string_format("failed to remove sequence %d with p0=%d, p1=%d\n", seq_id, p0, p1).c_str());
+    }
+}
+
+void common_context_seq_cp(llama_context * ctx, llama_seq_id seq_id_src, llama_seq_id seq_id_dst, llama_pos p0, llama_pos p1) {
+    auto * mem = llama_get_memory(ctx);
+    llama_memory_seq_cp(mem, seq_id_src, seq_id_dst, p0, p1);
+}
+
+void common_context_seq_add(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1, llama_pos delta) {
+    auto * mem = llama_get_memory(ctx);
+    llama_memory_seq_add(mem, seq_id, p0, p1, delta);
+}
+
 void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora) {
     std::vector<llama_adapter_lora *> loras;
     std::vector<float> scales;
@@ -1490,6 +1562,7 @@ struct llama_context_params common_context_params_to_llama(const common_params &
 
     cparams.n_ctx             = params.n_ctx;
     cparams.n_seq_max         = params.n_parallel;
+    cparams.n_rs_seq          = params.speculative.need_n_rs_seq();
     cparams.n_batch           = params.n_batch;
     cparams.n_ubatch          = params.n_ubatch;
     cparams.n_threads         = params.cpuparams.n_threads;
@@ -1960,3 +2033,110 @@ bool common_prompt_batch_decode(
 
     return true;
 }
+
+size_t common_prompt_checkpoint::size() const {
+    return data_tgt.size() + data_dft.size();
+}
+
+bool common_prompt_checkpoint::empty() const {
+    return data_tgt.empty();
+}
+
+void common_prompt_checkpoint::clear() {
+    n_tokens = 0;
+
+    pos_min = 0;
+    pos_max = 0;
+
+    data_tgt.clear();
+    data_dft.clear();
+}
+
+void common_prompt_checkpoint::update_pos(
+        int64_t n_tokens,
+        llama_pos pos_min,
+        llama_pos pos_max) {
+    this->n_tokens = n_tokens;
+    this->pos_min  = pos_min;
+    this->pos_max  = pos_max;
+}
+
+void common_prompt_checkpoint::update_tgt(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    const size_t ckpt_size = llama_state_seq_get_size_ext(ctx, seq_id, flags);
+
+    data_tgt.resize(ckpt_size);
+
+    const size_t n = llama_state_seq_get_data_ext(ctx, data_tgt.data(), ckpt_size, seq_id, flags);
+    if (n != ckpt_size) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", ckpt_size, n);
+    }
+}
+
+void common_prompt_checkpoint::update_dft(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    const size_t ckpt_size = llama_state_seq_get_size_ext(ctx, seq_id, flags);
+
+    data_dft.resize(ckpt_size);
+
+    const size_t n = llama_state_seq_get_data_ext(ctx, data_dft.data(), ckpt_size, seq_id, flags);
+    if (n != ckpt_size) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", ckpt_size, n);
+    }
+}
+
+void common_prompt_checkpoint::load_tgt(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) const {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    if (data_tgt.empty()) {
+        return;
+    }
+
+    const size_t n = llama_state_seq_set_data_ext(ctx, data_tgt.data(), data_tgt.size(), seq_id, flags);
+    if (n != data_tgt.size()) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", data_tgt.size(), n);
+    }
+}
+
+void common_prompt_checkpoint::load_dft(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) const {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    if (data_dft.empty()) {
+        return;
+    }
+
+    const size_t n = llama_state_seq_set_data_ext(ctx, data_dft.data(), data_dft.size(), seq_id, flags);
+    if (n != data_dft.size()) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", data_dft.size(), n);
+    }
+}
+
+void common_prompt_checkpoint::clear_tgt() {
+    data_tgt.clear();
+}
+
+void common_prompt_checkpoint::clear_dft() {
+    data_dft.clear();
+}

common/common.h

@@ -13,6 +13,7 @@
 #include <string_view>
 #include <vector>
 #include <map>
+#include <algorithm>
 
 #if defined(_WIN32) && !defined(_WIN32_WINNT)
 #define _WIN32_WINNT 0x0A00
@@ -157,9 +158,10 @@ enum common_params_sampling_config : uint64_t {
 
 enum common_speculative_type {
     COMMON_SPECULATIVE_TYPE_NONE,          // no speculative decoding
-    COMMON_SPECULATIVE_TYPE_DRAFT,         // draft model
-    COMMON_SPECULATIVE_TYPE_EAGLE3,        // eagle draft model
-    COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE,  // simple self-speculative decoding
+    COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE,  // standalone draft model speculative decoding
+    COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3,  // Eagle3 speculative decoding
+    COMMON_SPECULATIVE_TYPE_DRAFT_MTP,     // Multi-token prediction
+    COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE,  // simple self-speculative decoding based on n-grams
     COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K,   // self-speculative decoding with n-gram keys only
     COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V, // self-speculative decoding with n-gram keys and 4 m-gram values
     COMMON_SPECULATIVE_TYPE_NGRAM_MOD,
@@ -295,23 +297,21 @@ struct common_params_model {
     std::string name        = ""; // in format <user>/<model>[:<tag>] (tag is optional)     // NOLINT
 };
 
-struct common_ngram_mod;
-
 // draft-model-based speculative decoding parameters
 struct common_params_speculative_draft {
-    int32_t n_max = 16; // maximum number of tokens to draft during speculative decoding
-    int32_t n_min = 0;  // minimum number of draft tokens to use for speculative decoding
+    int32_t n_max = 3; // maximum number of tokens to draft during speculative decoding
+    int32_t n_min = 0; // minimum number of draft tokens to use for speculative decoding
 
-    float p_split = 0.1f;  // speculative decoding split probability
-    float p_min   = 0.75f; // minimum speculative decoding probability (greedy)
+    float p_split = 0.1f; // speculative decoding split probability
+    float p_min   = 0.0f; // minimum speculative decoding probability (greedy)
+
+    bool backend_sampling = true; // offload draft sampling to the backend (default: on)
 
     common_params_model mparams;
 
-    llama_model * model = nullptr; // a llama_model that can be shared by multiple speculative contexts
+    llama_context * ctx_tgt = nullptr;
+    llama_context * ctx_dft = nullptr;
 
-    llama_context_params cparams; // these are the parameters for the draft llama_context
-
-    int32_t n_ctx        = 0;  // draft context size
     int32_t n_gpu_layers = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
 
     ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
@@ -322,7 +322,6 @@ struct common_params_speculative_draft {
 
     std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
 
-    std::vector<std::pair<std::string, std::string>> replacements; // main to speculative model replacements
     std::vector<llama_model_tensor_buft_override> tensor_buft_overrides;
 };
 
@@ -331,9 +330,6 @@ struct common_params_speculative_ngram_mod {
 
     int32_t n_max = 64;
     int32_t n_min = 48;
-
-    // shared instance of the ngram container for all speculative decoding contexts
-    std::shared_ptr<common_ngram_mod> obj;
 };
 
 struct common_params_speculative_ngram_map {
@@ -348,9 +344,9 @@ struct common_params_speculative_ngram_cache {
 };
 
 struct common_params_speculative {
-    // TODO: become a vector in order to support "chains of speculators"
-    common_speculative_type type = COMMON_SPECULATIVE_TYPE_NONE;
+    std::vector<enum common_speculative_type> types = { COMMON_SPECULATIVE_TYPE_NONE };
 
+    // used by Simple, MTP, Eagle3, etc. - all methods that require some kind of draft model
     common_params_speculative_draft draft;
 
     common_params_speculative_ngram_mod ngram_mod;
@@ -363,6 +359,14 @@ struct common_params_speculative {
     bool has_dft() const {
         return !draft.mparams.path.empty() || !draft.mparams.hf_repo.empty();
     }
+
+    uint32_t need_n_rs_seq() const {
+        bool needs_rs_seq = std::any_of(types.begin(), types.end(), [&](auto t) {
+            return t == COMMON_SPECULATIVE_TYPE_DRAFT_MTP;
+        });
+
+        return needs_rs_seq ? draft.n_max : 0u;
+    }
 };
 
 struct common_params_vocoder {
@@ -590,7 +594,7 @@ struct common_params {
     bool    cache_prompt        = true;  // whether to enable prompt caching
     bool    cache_idle_slots    = true;  // save and clear idle slots upon starting a new task
     int32_t n_ctx_checkpoints   = 32;    // max number of context checkpoints per slot
-    int32_t checkpoint_every_nt = 8192;  // make a checkpoint every n tokens during prefill
+    int32_t checkpoint_min_step = 256;   // minimum spacing between context checkpoints
     int32_t cache_ram_mib       = 8192;  // -1 = no limit, 0 - disable, 1 = 1 MiB, etc.
 
     std::string hostname      = "127.0.0.1";
@@ -612,11 +616,17 @@ struct common_params {
 
     std::map<std::string, std::string> default_template_kwargs;
 
-    // webui configs
-    bool webui = true;
+    // UI configs
+    bool ui = true;
+
+    // Deprecated: use ui, ui_mcp_proxy, ui_config_json instead
+    bool webui = ui;
     bool webui_mcp_proxy = false;
     std::string webui_config_json;
 
+    bool ui_mcp_proxy = false;
+    std::string ui_config_json;
+
     // "advanced" endpoints are disabled by default for better security
     bool endpoint_slots   = true;
     bool endpoint_props   = false; // only control POST requests, not GET
@@ -694,6 +704,7 @@ struct common_params {
 // initializes the logging system and prints info about the build
 void common_init();
 
+void common_params_print_info(const common_params & params, bool print_devices = true);
 std::string common_params_get_system_info(const common_params & params);
 
 bool parse_cpu_range(const std::string & range, bool(&boolmask)[GGML_MAX_N_THREADS]);
@@ -720,6 +731,7 @@ std::string string_format(const char * fmt, ...);
 
 std::string string_strip(const std::string & str);
 std::string string_get_sortable_timestamp();
+std::string string_lcs(std::string_view a, std::string_view b);
 
 std::string string_join(const std::vector<std::string> & values, const std::string & separator);
 std::vector<std::string> string_split(const std::string & str, const std::string & delimiter);
@@ -844,7 +856,7 @@ struct common_sampler;
 
 // note: defines the model, context, samplers, ets. lifetimes
 struct common_init_result {
-    common_init_result(common_params & params);
+    common_init_result(common_params & params, bool model_only = false);
     ~common_init_result();
 
     llama_model * model();
@@ -862,7 +874,7 @@ private:
 
 using common_init_result_ptr = std::unique_ptr<common_init_result>;
 
-common_init_result_ptr common_init_from_params(common_params & params);
+common_init_result_ptr common_init_from_params(common_params & params, bool model_only = false);
 
 struct llama_model_params     common_model_params_to_llama  (      common_params & params);
 struct llama_context_params   common_context_params_to_llama(const common_params & params);
@@ -879,15 +891,20 @@ std::string common_get_model_endpoint();
 //
 
 enum common_context_seq_rm_type {
-    COMMON_CONTEXT_SEQ_RM_TYPE_NO   = 0, // seq_rm not supported (e.g. no memory module)
-    COMMON_CONTEXT_SEQ_RM_TYPE_PART = 1, // can seq_rm partial sequences
-    COMMON_CONTEXT_SEQ_RM_TYPE_FULL = 2, // can seq_rm full sequences only
+    COMMON_CONTEXT_SEQ_RM_TYPE_NO           = 0, // seq_rm not supported (e.g. no memory module)
+    COMMON_CONTEXT_SEQ_RM_TYPE_PART         = 1, // can seq_rm partial sequences
+    COMMON_CONTEXT_SEQ_RM_TYPE_FULL         = 2, // can seq_rm full sequences only
+    COMMON_CONTEXT_SEQ_RM_TYPE_RS = 3, // can seq_rm partial sequences, bounded by n_rs_seq
 };
 
 // check if the llama_context can remove sequences
 // note: clears the memory of the context
 common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx);
 
+// aborts execution on failure
+void common_context_seq_rm (llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1);
+void common_context_seq_add(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1, llama_pos delta);
+void common_context_seq_cp (llama_context * ctx, llama_seq_id seq_id_src, llama_seq_id seq_id_dst, llama_pos p0, llama_pos p1);
 
 //
 // Batch utils
@@ -1026,3 +1043,50 @@ ggml_opt_dataset_t common_opt_dataset_init(struct llama_context * ctx, const std
 
 // "adamw" or "sgd" (case insensitive)
 enum ggml_opt_optimizer_type common_opt_get_optimizer(const char *);
+
+//
+// prompt utils
+//
+
+struct common_prompt_checkpoint {
+    int64_t n_tokens;
+
+    llama_pos pos_min;
+    llama_pos pos_max;
+
+    std::vector<uint8_t> data_tgt;
+    std::vector<uint8_t> data_dft;
+
+    size_t size() const;
+
+    bool empty() const;
+    void clear();
+
+    void update_pos(
+            int64_t n_tokens,
+            llama_pos pos_min,
+            llama_pos pos_max);
+
+    void update_tgt(
+            llama_context * ctx,
+            llama_seq_id seq_id,
+            llama_state_seq_flags flags);
+
+    void update_dft(
+            llama_context * ctx,
+            llama_seq_id seq_id,
+            llama_state_seq_flags flags);
+
+    void load_tgt(
+            llama_context * ctx,
+            llama_seq_id seq_id,
+            llama_state_seq_flags flags) const;
+
+    void load_dft(
+            llama_context * ctx,
+            llama_seq_id seq_id,
+            llama_state_seq_flags flags) const;
+
+    void clear_tgt();
+    void clear_dft();
+};

common/download.cpp

@@ -320,9 +320,9 @@ static int common_download_file_single_online(const std::string & url,
 
     auto head = cli.Head(parts.path);
     if (!head || head->status < 200 || head->status >= 300) {
-        LOG_WRN("%s: HEAD failed, status: %d\n", __func__, head ? head->status : -1);
+        LOG_TRC("%s: HEAD failed, status: %d\n", __func__, head ? head->status : -1);
         if (file_exists) {
-            LOG_INF("%s: using cached file (HEAD failed): %s\n", __func__, path.c_str());
+            LOG_TRC("%s: using cached file (HEAD failed): %s\n", __func__, path.c_str());
             return 304; // 304 Not Modified - fake cached response
         }
         return head ? head->status : -1;
@@ -566,8 +566,11 @@ static hf_cache::hf_files get_split_files(const hf_cache::hf_files & files,
     return result;
 }
 
-static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
-                                          const std::string        & model) {
+// pick the best sibling GGUF whose filename contains `keyword` (e.g. "mmproj" / "mtp"),
+// preferring deeper shared directory prefix with the model, then closest quantization
+static hf_cache::hf_file find_best_sibling(const hf_cache::hf_files & files,
+                                           const std::string        & model,
+                                           const std::string        & keyword) {
     hf_cache::hf_file best;
     size_t best_depth = 0;
     int best_diff = 0;
@@ -579,20 +582,20 @@ static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
 
     for (const auto & f : files) {
         if (!string_ends_with(f.path, ".gguf") ||
-            f.path.find("mmproj") == std::string::npos) {
+            f.path.find(keyword) == std::string::npos) {
             continue;
         }
 
-        auto mmproj_parts = string_split<std::string>(f.path, '/');
-        auto mmproj_dir = mmproj_parts.end() - 1;
+        auto sib_parts = string_split<std::string>(f.path, '/');
+        auto sib_dir = sib_parts.end() - 1;
 
         auto [_, dir] = std::mismatch(model_parts.begin(), model_dir,
-                                      mmproj_parts.begin(), mmproj_dir);
-        if (dir != mmproj_dir) {
+                                      sib_parts.begin(), sib_dir);
+        if (dir != sib_dir) {
             continue;
         }
 
-        size_t depth = dir - mmproj_parts.begin();
+        size_t depth = dir - sib_parts.begin();
         auto bits = extract_quant_bits(f.path);
         auto diff = std::abs(bits - model_bits);
 
@@ -606,6 +609,16 @@ static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
     return best;
 }
 
+static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
+                                          const std::string        & model) {
+    return find_best_sibling(files, model, "mmproj");
+}
+
+static hf_cache::hf_file find_best_mtp(const hf_cache::hf_files & files,
+                                       const std::string        & model) {
+    return find_best_sibling(files, model, "mtp-");
+}
+
 static bool gguf_filename_is_model(const std::string & filepath) {
     if (!string_ends_with(filepath, ".gguf")) {
         return false;
@@ -617,7 +630,8 @@ static bool gguf_filename_is_model(const std::string & filepath) {
     }
 
     return filename.find("mmproj")  == std::string::npos &&
-           filename.find("imatrix") == std::string::npos;
+           filename.find("imatrix") == std::string::npos &&
+           filename.find("mtp-")    == std::string::npos;
 }
 
 static hf_cache::hf_file find_best_model(const hf_cache::hf_files & files,
@@ -673,11 +687,13 @@ struct hf_plan {
     hf_cache::hf_file primary;
     hf_cache::hf_files model_files;
     hf_cache::hf_file mmproj;
+    hf_cache::hf_file mtp;
 };
 
 static hf_plan get_hf_plan(const common_params_model  & model,
                            const common_download_opts & opts,
-                           bool download_mmproj) {
+                           bool download_mmproj,
+                           bool download_mtp) {
     hf_plan plan;
     hf_cache::hf_files all;
 
@@ -723,6 +739,10 @@ static hf_plan get_hf_plan(const common_params_model  & model,
         plan.mmproj = find_best_mmproj(all, primary.path);
     }
 
+    if (download_mtp) {
+        plan.mtp = find_best_mtp(all, primary.path);
+    }
+
     return plan;
 }
 
@@ -756,7 +776,8 @@ static std::vector<download_task> get_url_tasks(const common_params_model & mode
 
 common_download_model_result common_download_model(const common_params_model  & model,
                                                    const common_download_opts & opts,
-                                                   bool download_mmproj) {
+                                                   bool download_mmproj,
+                                                   bool download_mtp) {
     common_download_model_result result;
     std::vector<download_task> tasks;
     hf_plan hf;
@@ -764,13 +785,16 @@ common_download_model_result common_download_model(const common_params_model  &
     bool is_hf = !model.hf_repo.empty();
 
     if (is_hf) {
-        hf = get_hf_plan(model, opts, download_mmproj);
+        hf = get_hf_plan(model, opts, download_mmproj, download_mtp);
         for (const auto & f : hf.model_files) {
             tasks.push_back({f.url, f.local_path});
         }
         if (!hf.mmproj.path.empty()) {
             tasks.push_back({hf.mmproj.url, hf.mmproj.local_path});
         }
+        if (!hf.mtp.path.empty()) {
+            tasks.push_back({hf.mtp.url, hf.mtp.local_path});
+        }
     } else if (!model.url.empty()) {
         tasks = get_url_tasks(model);
     } else {
@@ -807,6 +831,10 @@ common_download_model_result common_download_model(const common_params_model  &
         if (!hf.mmproj.path.empty()) {
             result.mmproj_path = hf_cache::finalize_file(hf.mmproj);
         }
+
+        if (!hf.mtp.path.empty()) {
+            result.mtp_path = hf_cache::finalize_file(hf.mtp);
+        }
     } else {
         result.model_path = model.path;
     }
@@ -946,7 +974,8 @@ std::vector<common_cached_model_info> common_list_cached_models() {
     for (const auto & f : files) {
         auto split = get_gguf_split_info(f.path);
         if (split.index != 1 || split.tag.empty() ||
-            split.prefix.find("mmproj") != std::string::npos) {
+            split.prefix.find("mmproj") != std::string::npos ||
+            split.prefix.find("mtp-")   != std::string::npos) {
             continue;
         }
         if (seen.insert(f.repo_id + ":" + split.tag).second) {

common/download.h

@@ -59,6 +59,7 @@ struct common_download_opts {
 struct common_download_model_result {
     std::string model_path;
     std::string mmproj_path;
+    std::string mtp_path;
 };
 
 // Download model from HuggingFace repo or URL
@@ -83,12 +84,14 @@ struct common_download_model_result {
 // when opts.offline=true, no network requests are made
 // when download_mmproj=true, searches for mmproj in same directory as model or any parent directory
 // then with the closest quantization bits
+// when download_mtp=true, applies the same sibling search for an MTP-head GGUF
 //
-// returns result with model_path and mmproj_path (empty on failure)
+// returns result with model_path, mmproj_path and mtp_path (empty when not found / on failure)
 common_download_model_result common_download_model(
     const common_params_model & model,
     const common_download_opts & opts = {},
-    bool download_mmproj = false
+    bool download_mmproj = false,
+    bool download_mtp    = false
 );
 
 // returns list of cached models

common/fit.cpp

@@ -26,7 +26,7 @@ class common_params_fit_exception : public std::runtime_error {
     using std::runtime_error::runtime_error;
 };
 
-static std::vector<llama_device_memory_data> common_get_device_memory_data(
+std::vector<llama_device_memory_data> common_get_device_memory_data(
         const char * path_model,
         const llama_model_params * mparams,
         const llama_context_params * cparams,
@@ -109,16 +109,24 @@ static std::vector<llama_device_memory_data> common_get_device_memory_data(
         ret.back().total = total;
     }
     for (size_t i = 0; i < nd; i++) {
+        ggml_backend_dev_t dev = llama_model_get_device(model, i);
+
         size_t free;
         size_t total;
-        ggml_backend_dev_memory(llama_model_get_device(model, i), &free, &total);
+        ggml_backend_dev_memory(dev, &free, &total);
 
-        // devices can return 0 bytes for free and total memory if they do not
-        // have any to report. in this case, we will use the host memory as a fallback
-        // fixes: https://github.com/ggml-org/llama.cpp/issues/18577
+        // Some non-GPU accelerator backends, such as BLAS, report 0/0 and rely on
+        // the host-memory fallback. For GPU-like backends, keep 0/0 so --fit does
+        // not assign anything to a device with an unknown memory budget.
         if (free == 0 && total == 0) {
-            free  = ret.back().free;
-            total = ret.back().total;
+            const enum ggml_backend_dev_type type = ggml_backend_dev_type(dev);
+            if (type == GGML_BACKEND_DEVICE_TYPE_GPU || type == GGML_BACKEND_DEVICE_TYPE_IGPU) {
+                LOG_WRN("%s: device %s did not report memory; --fit will not use it\n",
+                        __func__, ggml_backend_dev_name(dev));
+            } else {
+                free  = ret.back().free;
+                total = ret.back().total;
+            }
         }
         ret[i].free  = free;
         ret[i].total = total;
@@ -160,7 +168,7 @@ static void common_params_fit_impl(
 
     // step 1: get data for default parameters and check whether any changes are necessary in the first place
 
-    LOG_INF("%s: getting device memory data for initial parameters:\n", __func__);
+    LOG_TRC("%s: getting device memory data for initial parameters:\n", __func__);
     const dmds_t dmds_full = common_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
     const size_t nd = devs.size(); // number of devices
 
@@ -205,13 +213,13 @@ static void common_params_fit_impl(
         LOG_INF("%s: projected to use %" PRId64 " MiB of host memory vs. %" PRId64 " MiB of total host memory\n",
             __func__, sum_projected_used/MiB, sum_free/MiB);
         if (sum_projected_free >= margins[0]) {
-            LOG_INF("%s: will leave %" PRId64 " >= %" PRId64 " MiB of system memory, no changes needed\n",
+            LOG_TRC("%s: will leave %" PRId64 " >= %" PRId64 " MiB of system memory, no changes needed\n",
                 __func__, sum_projected_free/MiB, margins[0]/MiB);
             return;
         }
     } else {
         if (nd > 1) {
-            LOG_INF("%s: projected memory use with initial parameters [MiB]:\n", __func__);
+            LOG_TRC("%s: projected memory use with initial parameters [MiB]:\n", __func__);
         }
         for (size_t id = 0; id < nd; id++) {
             const llama_device_memory_data & dmd = dmds_full[id];
@@ -226,16 +234,16 @@ static void common_params_fit_impl(
             sum_projected_model += dmd.mb.model;
 
             if (nd > 1) {
-                LOG_INF("%s:   - %s: %6" PRId64 " total, %6" PRId64 " used, %6" PRId64 " free vs. target of %6" PRId64 "\n",
+                LOG_TRC("%s:   - %s: %6" PRId64 " total, %6" PRId64 " used, %6" PRId64 " free vs. target of %6" PRId64 "\n",
                     __func__, dev_names[id].c_str(), dmd.total/MiB, projected_used/MiB, projected_free/MiB, margins[id]/MiB);
             }
         }
         assert(sum_free >= 0 && sum_projected_used >= 0);
-        LOG_INF("%s: projected to use %" PRId64 " MiB of device memory vs. %" PRId64 " MiB of free device memory\n",
+        LOG_TRC("%s: projected to use %" PRId64 " MiB of device memory vs. %" PRId64 " MiB of free device memory\n",
             __func__, sum_projected_used/MiB, sum_free/MiB);
         if (nd == 1) {
             if (projected_free_per_device[0] >= margins[0]) {
-                LOG_INF("%s: will leave %" PRId64 " >= %" PRId64 " MiB of free device memory, no changes needed\n",
+                LOG_TRC("%s: will leave %" PRId64 " >= %" PRId64 " MiB of free device memory, no changes needed\n",
                     __func__, projected_free_per_device[0]/MiB, margins[0]/MiB);
                 return;
             }
@@ -248,7 +256,7 @@ static void common_params_fit_impl(
                 }
             }
             if (!changes_needed) {
-                LOG_INF("%s: targets for free memory can be met on all devices, no changes needed\n", __func__);
+                LOG_TRC("%s: targets for free memory can be met on all devices, no changes needed\n", __func__);
                 return;
             }
         }
@@ -267,10 +275,10 @@ static void common_params_fit_impl(
         }
         if (global_surplus < 0) {
             if (nd <= 1) {
-                LOG_INF("%s: cannot meet free memory target of %" PRId64 " MiB, need to reduce device memory by %" PRId64 " MiB\n",
+                LOG_TRC("%s: cannot meet free memory target of %" PRId64 " MiB, need to reduce device memory by %" PRId64 " MiB\n",
                     __func__, margins[0]/MiB, -global_surplus/MiB);
             } else {
-                LOG_INF(
+                LOG_TRC(
                     "%s: cannot meet free memory targets on all devices, need to use %" PRId64 " MiB less in total\n",
                     __func__, -global_surplus/MiB);
             }
@@ -312,28 +320,28 @@ static void common_params_fit_impl(
 
                         const int64_t bytes_per_ctx = (sum_projected_used - sum_projected_used_min_ctx) / (hp_nct - n_ctx_min);
                         const int64_t memory_reduction = (hp_nct - cparams->n_ctx) * bytes_per_ctx;
-                        LOG_INF("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
+                        LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
                             __func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
                         if (nd <= 1) {
-                            LOG_INF("%s: entire model can be fit by reducing context\n", __func__);
+                            LOG_TRC("%s: entire model can be fit by reducing context\n", __func__);
                             return;
                         }
-                        LOG_INF("%s: entire model should be fit across devices by reducing context\n", __func__);
+                        LOG_TRC("%s: entire model should be fit across devices by reducing context\n", __func__);
                     } else {
                         const int64_t memory_reduction = sum_projected_used - sum_projected_used_min_ctx;
-                        LOG_INF("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
+                        LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
                             __func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
                     }
                 } else {
                     if (n_ctx_min == UINT32_MAX) {
-                        LOG_INF("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, hp_nct);
+                        LOG_TRC("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, hp_nct);
                     } else {
-                        LOG_INF("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
+                        LOG_TRC("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
                             __func__, hp_nct, n_ctx_min);
                     }
                 }
             } else {
-                LOG_INF("%s: context size set by user to %" PRIu32 " -> no change\n", __func__, cparams->n_ctx);
+                LOG_TRC("%s: context size set by user to %" PRIu32 " -> no change\n", __func__, cparams->n_ctx);
             }
         }
     }
@@ -477,10 +485,10 @@ static void common_params_fit_impl(
         const dmds_t dmd_nl = common_get_device_memory_data(
             path_model, &mparams_copy, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
 
-        LOG_INF("%s: memory for test allocation by device:\n", func_name);
+        LOG_TRC("%s: memory for test allocation by device:\n", func_name);
         for (size_t id = 0; id < nd; id++) {
             const ngl_t & n = ngl_per_device[id];
-            LOG_INF(
+            LOG_TRC(
                 "%s: id=%zu, n_layer=%2" PRIu32 ", n_part=%2" PRIu32 ", overflow_type=%d, mem=%6" PRId64 " MiB\n",
                 func_name, id, n.n_layer, n.n_part, int(n.overflow_type), dmd_nl[id].mb.total()/MiB);
         }
@@ -501,7 +509,7 @@ static void common_params_fit_impl(
         tensor_buft_overrides[1] = {nullptr, nullptr};
         mparams->tensor_buft_overrides = tensor_buft_overrides;
 
-        LOG_INF("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
+        LOG_TRC("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
         const dmds_t dmds_cpu_moe = common_get_device_memory_data(
             path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
 
@@ -511,10 +519,10 @@ static void common_params_fit_impl(
         }
 
         if (global_surplus_cpu_moe > 0) {
-            LOG_INF("%s: with only dense weights in device memory there is a total surplus of %" PRId64 " MiB\n",
+            LOG_TRC("%s: with only dense weights in device memory there is a total surplus of %" PRId64 " MiB\n",
                 __func__, global_surplus_cpu_moe/MiB);
         } else {
-            LOG_INF("%s: with only dense weights in device memory there is still a total deficit of %" PRId64 " MiB\n",
+            LOG_TRC("%s: with only dense weights in device memory there is still a total deficit of %" PRId64 " MiB\n",
                 __func__, -global_surplus_cpu_moe/MiB);
         }
 
@@ -527,7 +535,7 @@ static void common_params_fit_impl(
     targets.reserve(nd);
     for (size_t id = 0; id < nd; id++) {
         targets.push_back(dmds_full[id].free - margins[id]);
-        LOG_INF("%s: id=%zu, target=%" PRId64 " MiB\n", __func__, id, targets[id]/MiB);
+        LOG_TRC("%s: id=%zu, target=%" PRId64 " MiB\n", __func__, id, targets[id]/MiB);
     }
 
     std::vector<ggml_backend_buffer_type_t> overflow_bufts; // which bufts the first partial layer of a device overflows to:
@@ -547,9 +555,9 @@ static void common_params_fit_impl(
     //   - once we only have a difference of a single layer, stop and return the lower bound that just barely still fits
     //   - the last device has the output layer, which cannot be a partial layer
     if (hp_nex == 0) {
-        LOG_INF("%s: filling dense layers back-to-front:\n", __func__);
+        LOG_TRC("%s: filling dense layers back-to-front:\n", __func__);
     } else {
-        LOG_INF("%s: filling dense-only layers back-to-front:\n", __func__);
+        LOG_TRC("%s: filling dense-only layers back-to-front:\n", __func__);
     }
     for (int id = nd - 1; id >= 0; id--) {
         uint32_t n_unassigned = hp_ngl + 1;
@@ -568,7 +576,7 @@ static void common_params_fit_impl(
             if (mem_high[id] > targets[id]) {
                 assert(ngl_per_device_high[id].n_layer > ngl_per_device[id].n_layer);
                 uint32_t delta = ngl_per_device_high[id].n_layer - ngl_per_device[id].n_layer;
-                LOG_INF("%s: start filling device %" PRIu32 ", delta=%" PRIu32 "\n", __func__, id, delta);
+                LOG_TRC("%s: start filling device %" PRIu32 ", delta=%" PRIu32 "\n", __func__, id, delta);
                 while (delta > 1) {
                     uint32_t step_size = int64_t(delta) * (targets[id] - mem[id]) / (mem_high[id] - mem[id]);
                     step_size = std::max(step_size, uint32_t(1));
@@ -585,11 +593,11 @@ static void common_params_fit_impl(
                     if (mem_test[id] <= targets[id]) {
                         ngl_per_device = ngl_per_device_test;
                         mem            = mem_test;
-                        LOG_INF("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
+                        LOG_TRC("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
                     } else {
                         ngl_per_device_high = ngl_per_device_test;
                         mem_high            = mem_test;
-                        LOG_INF("%s: set ngl_per_device_high[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device_high[id].n_layer);
+                        LOG_TRC("%s: set ngl_per_device_high[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device_high[id].n_layer);
                     }
                     delta = ngl_per_device_high[id].n_layer - ngl_per_device[id].n_layer;
                 }
@@ -597,12 +605,12 @@ static void common_params_fit_impl(
                 assert(ngl_per_device_high[id].n_layer == n_unassigned);
                 ngl_per_device = ngl_per_device_high;
                 mem            = mem_high;
-                LOG_INF("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
+                LOG_TRC("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
             }
         }
 
         const int64_t projected_margin = dmds_full[id].free - mem[id];
-        LOG_INF(
+        LOG_TRC(
             "%s:   - %s: %2" PRIu32 " layers, %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
             __func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, mem[id]/MiB, projected_margin/MiB);
     }
@@ -626,7 +634,7 @@ static void common_params_fit_impl(
     }
     assert(id_dense_start < nd);
 
-    LOG_INF("%s: converting dense-only layers to full layers and filling them front-to-back with overflow to next device/system memory:\n", __func__);
+    LOG_TRC("%s: converting dense-only layers to full layers and filling them front-to-back with overflow to next device/system memory:\n", __func__);
     for (size_t id = 0; id <= id_dense_start && id_dense_start < nd; id++) {
         std::vector<ngl_t> ngl_per_device_high = ngl_per_device;
         for (size_t jd = id_dense_start; jd < nd; jd++) {
@@ -666,13 +674,13 @@ static void common_params_fit_impl(
                     ngl_per_device = ngl_per_device_test;
                     mem            = mem_test;
                     id_dense_start = id_dense_start_test;
-                    LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
+                    LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
                         __func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
                 } else {
                     ngl_per_device_high = ngl_per_device_test;
                     mem_high            = mem_test;
                     id_dense_start_high = id_dense_start_test;
-                    LOG_INF("%s: set ngl_per_device_high[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start_high=%zu\n",
+                    LOG_TRC("%s: set ngl_per_device_high[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start_high=%zu\n",
                         __func__, id, ngl_per_device_high[id].n_layer, ngl_per_device_high[id].n_part, id_dense_start_high);
                 }
                 assert(ngl_per_device_high[id].n_full() >= ngl_per_device[id].n_full());
@@ -682,7 +690,7 @@ static void common_params_fit_impl(
             ngl_per_device = ngl_per_device_high;
             mem            = mem_high;
             id_dense_start = id_dense_start_high;
-            LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
+            LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
                 __func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
         }
 
@@ -702,44 +710,44 @@ static void common_params_fit_impl(
             if (id < nd - 1) {
                 overflow_bufts_test[id] = ggml_backend_dev_buffer_type(devs[id + 1]);
             }
-            LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_UP\n", __func__);
+            LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_UP\n", __func__);
             std::vector<int64_t> mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
             if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
                 ngl_per_device = ngl_per_device_test;
                 overflow_bufts = overflow_bufts_test;
                 mem            = mem_test;
                 id_dense_start = id_dense_start_test;
-                LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", UP), id_dense_start=%zu\n",
+                LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", UP), id_dense_start=%zu\n",
                     __func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
 
                 ngl_per_device_test[id].overflow_type = LAYER_FRACTION_GATE;
-                LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_GATE\n", __func__);
+                LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_GATE\n", __func__);
                 mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
                 if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
                     ngl_per_device = ngl_per_device_test;
                     overflow_bufts = overflow_bufts_test;
                     mem            = mem_test;
                     id_dense_start = id_dense_start_test;
-                    LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", GATE), id_dense_start=%zu\n",
+                    LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", GATE), id_dense_start=%zu\n",
                         __func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
                 }
             } else {
                 ngl_per_device_test[id].overflow_type = LAYER_FRACTION_ATTN;
-                LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_ATTN\n", __func__);
+                LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_ATTN\n", __func__);
                 mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
                 if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
                     ngl_per_device = ngl_per_device_test;
                     overflow_bufts = overflow_bufts_test;
                     mem            = mem_test;
                     id_dense_start = id_dense_start_test;
-                    LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", ATTN), id_dense_start=%zu\n",
+                    LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", ATTN), id_dense_start=%zu\n",
                         __func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
                 }
             }
         }
 
         const int64_t projected_margin = dmds_full[id].free - mem[id];
-        LOG_INF(
+        LOG_TRC(
             "%s:   - %s: %2" PRIu32 " layers (%2" PRIu32 " overflowing), %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
             __func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, ngl_per_device[id].n_part, mem[id]/MiB, projected_margin/MiB);
     }
@@ -747,7 +755,7 @@ static void common_params_fit_impl(
     // print info for devices that were not changed during the conversion from dense only to full layers:
     for (size_t id = id_dense_start + 1; id < nd; id++) {
         const int64_t projected_margin = dmds_full[id].free - mem[id];
-        LOG_INF(
+        LOG_TRC(
             "%s:   - %s: %2" PRIu32 " layers (%2" PRIu32 " overflowing), %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
             __func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, ngl_per_device[id].n_part, mem[id]/MiB, projected_margin/MiB);
     }
@@ -768,7 +776,7 @@ enum common_params_fit_status common_fit_params(
     common_params_fit_status status = COMMON_PARAMS_FIT_STATUS_SUCCESS;
     try {
         common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, log_level);
-        LOG_INF("%s: successfully fit params to free device memory\n", __func__);
+        LOG_TRC("%s: successfully fit params to free device memory\n", __func__);
     } catch (const common_params_fit_exception & e) {
         LOG_WRN("%s: failed to fit params to free device memory: %s\n", __func__, e.what());
         status = COMMON_PARAMS_FIT_STATUS_FAILURE;
@@ -777,7 +785,7 @@ enum common_params_fit_status common_fit_params(
         status = COMMON_PARAMS_FIT_STATUS_ERROR;
     }
     const int64_t t1_us = llama_time_us();
-    LOG_INF("%s: fitting params to free memory took %.2f seconds\n", __func__, (t1_us - t0_us) * 1e-6);
+    LOG_TRC("%s: fitting params to free memory took %.2f seconds\n", __func__, (t1_us - t0_us) * 1e-6);
     return status;
 }
 
@@ -917,7 +925,7 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
         }
     }
     for (const auto & td : table_data) {
-        LOG_INF(td[0].c_str(),
+        LOG_TRC(td[0].c_str(),
             __func__, td[1].c_str(), td[2].c_str(), td[3].c_str(), td[4].c_str(), td[5].c_str(),
             td[6].c_str(), td[7].c_str(), td[8].c_str());
     }

common/fit.h

@@ -1,6 +1,11 @@
 #pragma once
 
 #include "ggml.h"
+#include "ggml-backend.h"
+#include "llama.h"
+#include "../src/llama-ext.h"
+
+#include <vector>
 
 enum common_params_fit_status {
     COMMON_PARAMS_FIT_STATUS_SUCCESS = 0, // found allocations that are projected to fit
@@ -30,3 +35,14 @@ void common_fit_print(
                 struct llama_context_params * cparams);
 
 void common_memory_breakdown_print(const struct llama_context * ctx);
+
+// Load a model + context with no_alloc and return the per-device memory breakdown.
+std::vector<llama_device_memory_data> common_get_device_memory_data(
+                                  const char   * path_model,
+        const struct llama_model_params         * mparams,
+        const struct llama_context_params       * cparams,
+        std::vector<ggml_backend_dev_t>         & devs,
+                                      uint32_t  & hp_ngl,
+                                      uint32_t  & hp_n_ctx_train,
+                                      uint32_t  & hp_n_expert,
+                           enum ggml_log_level    log_level);

common/hf-cache.cpp

@@ -11,7 +11,6 @@
 #include <filesystem>
 #include <fstream>
 #include <atomic>
-#include <regex> // migration only
 #include <string>
 #include <string_view>
 #include <stdexcept>
@@ -57,7 +56,7 @@ static fs::path get_cache_directory() {
 #ifndef _WIN32
         const struct passwd * pw = getpwuid(getuid());
 
-        if (pw->pw_dir && *pw->pw_dir) {
+        if (pw && pw->pw_dir && *pw->pw_dir) {
             return fs::path(pw->pw_dir) / ".cache" / "huggingface" / "hub";
         }
 #endif
@@ -336,15 +335,9 @@ hf_files get_repo_files(const std::string & repo_id,
                 if (item["lfs"].contains("oid") && item["lfs"]["oid"].is_string()) {
                     file.oid = item["lfs"]["oid"].get<std::string>();
                 }
-                if (item["lfs"].contains("size") && item["lfs"]["size"].is_number()) {
-                    file.size = item["lfs"]["size"].get<size_t>();
-                }
             } else if (item.contains("oid") && item["oid"].is_string()) {
                 file.oid = item["oid"].get<std::string>();
             }
-            if (file.size == 0 && item.contains("size") && item["size"].is_number()) {
-                file.size = item["size"].get<size_t>();
-            }
 
             if (!file.oid.empty() && !is_valid_oid(file.oid)) {
                 LOG_WRN("%s: skip invalid oid: %s\n", __func__, file.oid.c_str());
@@ -502,271 +495,4 @@ std::string finalize_file(const hf_file & file) {
     return file.final_path;
 }
 
-// delete everything after this line, one day
-
-// copied from download.cpp without the tag part
-struct gguf_split_info {
-    std::string prefix; // tag included
-    int index;
-    int count;
-};
-
-static gguf_split_info get_gguf_split_info(const std::string & path) {
-    static const std::regex re_split("^(.+)-([0-9]{5})-of-([0-9]{5})$", std::regex::icase);
-    std::smatch m;
-
-    std::string prefix = path;
-    if (!string_remove_suffix(prefix, ".gguf")) {
-        return {};
-    }
-
-    int index = 1;
-    int count = 1;
-
-    if (std::regex_match(prefix, m, re_split)) {
-        index = std::stoi(m[2].str());
-        count = std::stoi(m[3].str());
-        prefix = m[1].str();
-    }
-
-    return {std::move(prefix), index, count};
-}
-
-static std::pair<std::string, std::string> parse_manifest_name(std::string & filename) {
-    static const std::regex re(R"(^manifest=([^=]+)=([^=]+)=.*\.json$)");
-    std::smatch match;
-    if (std::regex_match(filename, match, re)) {
-        return {match[1].str(), match[2].str()};
-    }
-    return {};
-}
-
-static std::string make_old_cache_filename(const std::string & owner,
-                                           const std::string & repo,
-                                           const std::string & filename) {
-    auto result = owner + "_" + repo + "_" + filename;
-    string_replace_all(result, "/", "_");
-    return result;
-}
-
-struct migrate_file {
-    std::string path;
-    std::string sha256;
-    size_t size;
-    fs::path old_path;
-    fs::path etag_path;
-    const hf_file * file;
-};
-
-using migrate_files = std::vector<migrate_file>;
-
-static bool collect_file(const fs::path    & old_cache,
-                         const std::string & owner,
-                         const std::string & repo,
-                         const std::string & path,
-                         const std::string & sha256,
-                         const hf_files    & files,
-                         migrate_files     & to_migrate) {
-
-    const hf_file * file = nullptr;
-
-    for (const auto & f : files) {
-        if (f.path == path) {
-            file = &f;
-            break;
-        }
-    }
-
-    std::string old_filename = make_old_cache_filename(owner, repo, path);
-    fs::path old_path = old_cache / old_filename;
-    fs::path etag_path = old_path.string() + ".etag";
-
-    if (!fs::exists(old_path)) {
-        if (file && fs::exists(file->final_path)) {
-            return true;
-        }
-        LOG_WRN("%s: %s not found in old cache or HF cache\n", __func__, old_filename.c_str());
-        return false;
-    }
-
-    if (!file) {
-        LOG_WRN("%s: %s not found in current repo\n", __func__, old_filename.c_str());
-        return false;
-    }
-
-    if (!sha256.empty() && !file->oid.empty() && sha256 != file->oid) {
-        LOG_WRN("%s: %s is not up to date (sha256 mismatch)\n", __func__, old_filename.c_str());
-        return false;
-    }
-
-    if (file->size > 0) {
-        size_t size = fs::file_size(old_path);
-        if (size != file->size) {
-            LOG_WRN("%s: %s has wrong size %zu (expected %zu)\n", __func__, old_filename.c_str(), size, file->size);
-            return false;
-        }
-    }
-
-    to_migrate.push_back({path, sha256, file->size, old_path, etag_path, file});
-    return true;
-}
-
-static bool collect_files(const fs::path    & old_cache,
-                          const std::string & owner,
-                          const std::string & repo,
-                          const nl::json    & node,
-                          const hf_files    & files,
-                          migrate_files     & to_migrate) {
-
-    if (!node.contains("rfilename") ||
-        !node.contains("lfs")       ||
-        !node["lfs"].contains("sha256")) {
-        return true;
-    }
-
-    std::string path = node["rfilename"];
-    std::string sha256 = node["lfs"]["sha256"];
-
-    auto split = get_gguf_split_info(path);
-
-    if (split.count <= 1) {
-        return collect_file(old_cache, owner, repo, path, sha256, files, to_migrate);
-    }
-
-    std::vector<std::pair<std::string, std::string>> splits;
-
-    for (const auto & f : files) {
-        auto split_f = get_gguf_split_info(f.path);
-        if (split_f.count == split.count && split_f.prefix == split.prefix) {
-            // sadly the manifest only provides the sha256 of the first file (index == 1)
-            // the rest will be verified using the size...
-            std::string f_sha256 = (split_f.index == 1) ? sha256 : "";
-            splits.emplace_back(f.path, f_sha256);
-        }
-    }
-
-    if ((int)splits.size() != split.count) {
-        LOG_WRN("%s: expected %d split files but found %d in repo\n", __func__, split.count, (int)splits.size());
-        return false;
-    }
-
-    for (const auto & [f_path, f_sha256] : splits) {
-        if (!collect_file(old_cache, owner, repo, f_path, f_sha256, files, to_migrate)) {
-            return false;
-        }
-    }
-
-    return true;
-}
-
-static bool migrate_file(const migrate_file & file) {
-    std::error_code ec;
-
-    fs::path new_path(file.file->local_path);
-    fs::create_directories(new_path.parent_path(), ec);
-
-    if (!fs::exists(new_path, ec)) {
-        fs::rename(file.old_path, new_path, ec);
-        if (ec) {
-            fs::copy_file(file.old_path, new_path, ec);
-            if (ec) {
-                LOG_ERR("%s: failed to move/copy %s: %s\n", __func__, file.old_path.string().c_str(), ec.message().c_str());
-                return false;
-            }
-        }
-        fs::remove(file.old_path, ec);
-    }
-    fs::remove(file.etag_path, ec);
-
-    std::string filename = finalize_file(*file.file);
-    LOG_INF("%s: migrated %s -> %s\n", __func__, file.old_path.filename().string().c_str(), filename.c_str());
-    return true;
-}
-
-void migrate_old_cache_to_hf_cache(const std::string & token, bool offline) {
-    fs::path old_cache = fs_get_cache_directory();
-    if (!fs::exists(old_cache)) {
-        return;
-    }
-
-    if (offline) {
-        LOG_WRN("%s: skipping migration in offline mode (will run when online)\n", __func__);
-        return; // -hf is not going to work
-    }
-
-    bool warned = false;
-
-    for (const auto & entry : fs::directory_iterator(old_cache)) {
-        if (!entry.is_regular_file()) {
-            continue;
-        }
-        auto filename = entry.path().filename().string();
-        auto [owner, repo] = parse_manifest_name(filename);
-
-        if (owner.empty() || repo.empty()) {
-            continue;
-        }
-
-        if (!warned) {
-            warned = true;
-            LOG_WRN("================================================================================\n"
-                    "WARNING: Migrating cache to HuggingFace cache directory\n"
-                    "  Old cache: %s\n"
-                    "  New cache: %s\n"
-                    "This one-time migration moves models previously downloaded with -hf\n"
-                    "from the legacy llama.cpp cache to the standard HuggingFace cache.\n"
-                    "Models downloaded with --model-url are not affected.\n"
-                    "================================================================================\n",
-                    old_cache.string().c_str(), get_cache_directory().string().c_str());
-        }
-
-        auto repo_id = owner + "/" + repo;
-        auto files = get_repo_files(repo_id, token);
-
-        if (files.empty()) {
-            LOG_WRN("%s: could not get repo files for %s, skipping\n", __func__, repo_id.c_str());
-            continue;
-        }
-
-        migrate_files to_migrate;
-        bool ok = true;
-
-        try {
-            std::ifstream manifest(entry.path());
-            auto json = nl::json::parse(manifest);
-            for (const char * key : {"ggufFile", "mmprojFile"}) {
-                if (json.contains(key)) {
-                    if (!collect_files(old_cache, owner, repo, json[key], files, to_migrate)) {
-                        ok = false;
-                        break;
-                    }
-                }
-            }
-        } catch (const std::exception & e) {
-            LOG_WRN("%s: failed to parse manifest %s: %s\n", __func__, filename.c_str(), e.what());
-            continue;
-        }
-
-        if (!ok) {
-            LOG_WRN("%s: migration skipped: one or more files failed validation\n", __func__);
-            continue;
-        }
-
-        for (const auto & file : to_migrate) {
-            if (!migrate_file(file)) {
-                ok = false;
-                break;
-            }
-        }
-
-        if (!ok) {
-            LOG_WRN("%s: migration failed: could not migrate all files\n", __func__);
-            continue;
-        }
-
-        LOG_INF("%s: migration complete, deleting manifest: %s\n", __func__, entry.path().string().c_str());
-        fs::remove(entry.path());
-    }
-}
-
 } // namespace hf_cache

common/hf-cache.h

@@ -14,7 +14,6 @@ struct hf_file {
     std::string final_path;
     std::string oid;
     std::string repo_id;
-    size_t size = 0; // only for the migration
 };
 
 using hf_files = std::vector<hf_file>;
@@ -30,7 +29,4 @@ hf_files get_cached_files(const std::string & repo_id = {});
 // Create snapshot path (link or move/copy) and return it
 std::string finalize_file(const hf_file & file);
 
-// TODO: Remove later
-void migrate_old_cache_to_hf_cache(const std::string & token, bool offline = false);
-
 } // namespace hf_cache

common/log.cpp

@@ -435,10 +435,10 @@ void common_log_flush(struct common_log * log) {
 static int common_get_verbosity(enum ggml_log_level level) {
     switch (level) {
         case GGML_LOG_LEVEL_DEBUG: return LOG_LEVEL_DEBUG;
-        case GGML_LOG_LEVEL_INFO:  return LOG_LEVEL_INFO;
+        case GGML_LOG_LEVEL_INFO:  return LOG_LEVEL_TRACE;
         case GGML_LOG_LEVEL_WARN:  return LOG_LEVEL_WARN;
         case GGML_LOG_LEVEL_ERROR: return LOG_LEVEL_ERROR;
-        case GGML_LOG_LEVEL_CONT:  return LOG_LEVEL_INFO; // same as INFO
+        case GGML_LOG_LEVEL_CONT:  return LOG_LEVEL_TRACE;
         case GGML_LOG_LEVEL_NONE:
         default:
             return LOG_LEVEL_OUTPUT;

common/log.h

@@ -21,7 +21,8 @@
 #    define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
 #endif
 
-#define LOG_LEVEL_DEBUG  4
+#define LOG_LEVEL_DEBUG  5
+#define LOG_LEVEL_TRACE  4
 #define LOG_LEVEL_INFO   3
 #define LOG_LEVEL_WARN   2
 #define LOG_LEVEL_ERROR  1
@@ -111,13 +112,15 @@ void common_log_flush         (struct common_log * log);                    // f
 #define LOGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_NONE, verbosity,        __VA_ARGS__)
 
 #define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, LOG_LEVEL_DEBUG,  __VA_ARGS__)
+#define LOG_TRC(...) LOG_TMPL(GGML_LOG_LEVEL_INFO,  LOG_LEVEL_TRACE,  __VA_ARGS__)
 #define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO,  LOG_LEVEL_INFO,   __VA_ARGS__)
 #define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN,  LOG_LEVEL_WARN,   __VA_ARGS__)
 #define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, LOG_LEVEL_ERROR,  __VA_ARGS__)
 #define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT,  LOG_LEVEL_INFO,   __VA_ARGS__) // same as INFO
 
+#define LOG_DBGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, verbosity, __VA_ARGS__)
+#define LOG_TRCV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_TRACE, verbosity, __VA_ARGS__)
 #define LOG_INFV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_INFO,  verbosity, __VA_ARGS__)
 #define LOG_WRNV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_WARN,  verbosity, __VA_ARGS__)
 #define LOG_ERRV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, verbosity, __VA_ARGS__)
-#define LOG_DBGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, verbosity, __VA_ARGS__)
 #define LOG_CNTV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_CONT,  verbosity, __VA_ARGS__)

common/ngram-map.cpp

@@ -471,7 +471,7 @@ void common_ngram_map_draft(common_ngram_map & map,
         sum_occur += curr_occur;
     }
 
-    LOG_INF("%s: key_offset = %zu, max_occur = %d, sum_occur = %d, slot_max = %d [%zu/%d, %zu/%d, %zu/%d, %zu/%d]\n", __func__,
+    LOG_DBG("%s: key_offset = %zu, max_occur = %d, sum_occur = %d, slot_max = %d [%zu/%d, %zu/%d, %zu/%d, %zu/%d]\n", __func__,
             key_offset,
             max_occur, sum_occur, slot_max,
             curr_key.values[0].value_idx, curr_key.values[0].value_num,
@@ -482,7 +482,7 @@ void common_ngram_map_draft(common_ngram_map & map,
     // Print the tokens of the four values (if idx != 0), use LOG_INF
     for (int v = 0; v < COMMON_NGRAM_MAX_VALUES; ++v) {
         if (curr_key.values[v].value_idx != 0) {
-            LOG_INF("%s: value[%d] = %s\n", __func__, v, common_tokens_to_str(inp, curr_key.values[v].value_idx, m).c_str());
+            LOG_DBG("%s: value[%d] = %s\n", __func__, v, common_tokens_to_str(inp, curr_key.values[v].value_idx, m).c_str());
         }
     }
 
@@ -500,7 +500,7 @@ void common_ngram_map_draft(common_ngram_map & map,
         draft.push_back(inp[match_pos + n + i]);
     }
 
-    LOG_INF("%s: key_offset = %zu, slot_max = %d, key_num = %d, draft.size = %zu\n", __func__,
+    LOG_DBG("%s: key_offset = %zu, slot_max = %d, key_num = %d, draft.size = %zu\n", __func__,
             key_offset, slot_max,
             curr_key.key_num, draft.size());
 

common/preset.cpp

@@ -163,8 +163,13 @@ void common_preset::merge(const common_preset & other) {
     }
 }
 
-void common_preset::apply_to_params(common_params & params) const {
+void common_preset::apply_to_params(common_params & params, const std::set<std::string> & handled_keys) const {
     for (const auto & [opt, val] : options) {
+        if (!handled_keys.empty()) {
+            if (!opt.env || handled_keys.find(opt.env) == handled_keys.end()) {
+                continue;
+            }
+        }
         // apply each option to params
         if (opt.handler_string) {
             opt.handler_string(params, val);

common/preset.h

@@ -43,7 +43,8 @@ struct common_preset {
     void merge(const common_preset & other);
 
     // apply preset options to common_params
-    void apply_to_params(common_params & params) const;
+    // optionally specify handled_keys to only apply a subset of options (identified by their env), if empty, apply all options
+    void apply_to_params(common_params & params, const std::set<std::string> & handled_keys = std::set<std::string>()) const;
 };
 
 // interface for multiple presets in one file

common/reasoning-budget.cpp

@@ -171,22 +171,12 @@ static void common_reasoning_budget_reset(struct llama_sampler * smpl) {
     ctx->force_pos = 0;
 }
 
-// forward declaration for use in clone
 static struct llama_sampler * common_reasoning_budget_init_state(
         const struct llama_vocab * vocab, const std::vector<llama_token> & start_tokens,
         const std::vector<llama_token> & end_tokens, const std::vector<llama_token> & forced_tokens,
         int32_t budget, common_reasoning_budget_state initial_state);
 
-static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl) {
-    const auto * ctx = (const common_reasoning_budget_ctx *) smpl->ctx;
-    return common_reasoning_budget_init_state(
-        ctx->vocab,
-        ctx->start_matcher.tokens,
-        ctx->end_matcher.tokens,
-        ctx->forced_tokens,
-        ctx->budget,
-        ctx->state);
-}
+static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl);
 
 static void common_reasoning_budget_free(struct llama_sampler * smpl) {
     delete (common_reasoning_budget_ctx *) smpl->ctx;
@@ -205,6 +195,15 @@ static struct llama_sampler_i common_reasoning_budget_i = {
     /* .backend_set_input = */ nullptr,
 };
 
+static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl) {
+    const auto * ctx = (const common_reasoning_budget_ctx *) smpl->ctx;
+
+    return llama_sampler_init(
+        /* .iface = */ &common_reasoning_budget_i,
+        /* .ctx   = */ new common_reasoning_budget_ctx(*ctx)
+    );
+}
+
 static struct llama_sampler * common_reasoning_budget_init_state(
         const struct llama_vocab             * vocab,
         const std::vector<llama_token>       & start_tokens,

common/sampling.cpp

@@ -547,6 +547,8 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
     auto & chain = gsmpl->chain;
     auto & cur_p = gsmpl->cur_p; // initialized by set_logits
 
+    gsmpl->set_logits(ctx, idx);
+
     // Check if a backend sampler has already sampled a token in which case we
     // return that token id directly.
     {
@@ -558,17 +560,17 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
             GGML_ASSERT(!gsmpl->grmr    && "using grammar in combination with backend sampling is not supported");
             GGML_ASSERT(!gsmpl->rbudget && "using reasoning budget in combination with backend sampling is not supported");
 
-            // TODO: simplify
-            gsmpl->cur.resize(1);
-            gsmpl->cur[0] = { id, 0.0f, 1.0f };
-            cur_p = { gsmpl->cur.data(), gsmpl->cur.size(), 0, true };
+            for (size_t i = 0; i < cur_p.size; ++i) {
+                if (cur_p.data[i].id == id) {
+                    cur_p.selected = i;
+                    break;
+                }
+            }
 
             return id;
         }
     }
 
-    gsmpl->set_logits(ctx, idx);
-
     // apply reasoning budget first
     llama_sampler_apply(rbudget, &cur_p);
 

common/speculative.h

@@ -5,8 +5,14 @@
 
 struct common_speculative;
 
+// comma separated list the provided types
+std::string common_speculative_type_name_str(const std::vector<enum common_speculative_type> & types);
+
 // comma separated list of all types
-std::string common_speculative_type_name_str();
+const char * common_speculative_all_types_str();
+
+// parse user provided types
+std::vector<enum common_speculative_type> common_speculative_types_from_names(const std::vector<std::string> & names);
 
 // convert string to type
 enum common_speculative_type common_speculative_type_from_name(const std::string & name);
@@ -14,27 +20,50 @@ enum common_speculative_type common_speculative_type_from_name(const std::string
 // convert type to string
 std::string common_speculative_type_to_str(enum common_speculative_type type);
 
-common_speculative * common_speculative_init(
-        common_params_speculative & params,
-        llama_context             * ctx_tgt);
+common_speculative * common_speculative_init(common_params_speculative & params, uint32_t n_seq);
 
 void common_speculative_free(common_speculative * spec);
 
+struct common_speculative_draft_params {
+    // this flag is used to chain the drafts through all the available implementations
+    // after the first successful draft from an implementation, we set it
+    //   to false to prevent further drafts for that sequence
+    // at the end of the draft() call, all drafting flags will be reset to false
+    bool drafting = false;
+
+    // overrides individual configurations (-1 disabled)
+    // can be used to constraint the max draft based on the remaining context size
+    int32_t n_max = -1;
+
+    llama_pos   n_past;
+    llama_token id_last;
+
+    // TODO: remove in the future by keeping track of the prompt from the _begin() call and the consecutive accept calls
+    const llama_tokens * prompt;
+
+    // the generated draft from the last _draft() call
+    llama_tokens * result;
+};
+
+common_speculative_draft_params & common_speculative_get_draft_params(common_speculative * spec, llama_seq_id seq_id);
+
 // optionally call once at the beginning of a new generation
-void common_speculative_begin(common_speculative * spec, const llama_tokens & prompt);
+void common_speculative_begin(common_speculative * spec, llama_seq_id seq_id, const llama_tokens & prompt);
 
-// sample up to n_draft tokens and add them to the batch using the draft model
-llama_tokens common_speculative_draft(
-                     common_speculative * spec,
-        const common_params_speculative & params,
-                     const llama_tokens & prompt,
-                            llama_token   id_last);
+// process the batch and update the internal state of the speculative context
+bool common_speculative_process(common_speculative * spec, const llama_batch & batch);
 
-// informs the speculative decoder that n_accepted tokens were accepted by the target model
-void common_speculative_accept(common_speculative * spec, uint16_t n_accepted);
+// true if any implementation requires target post-norm embeddings to be extracted
+bool common_speculative_need_embd(common_speculative * spec);
 
-int32_t common_speculative_n_max(const common_speculative * spec, const common_params_speculative & params);
-int32_t common_speculative_n_min(const common_speculative * spec, const common_params_speculative & params);
+// true if any implementation requires target pre-norm embeddings to be extracted
+bool common_speculative_need_embd_pre_norm(common_speculative * spec);
+
+// generate drafts for the sequences specified with `common_speculative_get_draft_params`
+void common_speculative_draft(common_speculative * spec);
+
+// informs the speculative context that n_accepted tokens were accepted by the target model
+void common_speculative_accept(common_speculative * spec, llama_seq_id, uint16_t n_accepted);
 
 // print statistics about the speculative decoding
 void common_speculative_print_stats(const common_speculative * spec);

conversion/__init__.py

@@ -0,0 +1,333 @@
+from __future__ import annotations
+
+from .base import (
+    ModelBase, TextModel, MmprojModel, ModelType, SentencePieceTokenTypes,
+    logger, _mistral_common_installed, _mistral_import_error_msg,
+    get_model_architecture, LazyTorchTensor,
+)
+from typing import Type
+
+
+__all__ = [
+    "ModelBase", "TextModel", "MmprojModel", "ModelType", "SentencePieceTokenTypes",
+    "get_model_architecture", "LazyTorchTensor", "logger",
+    "_mistral_common_installed", "_mistral_import_error_msg",
+    "get_model_class", "print_registered_models", "load_all_models",
+]
+
+
+TEXT_MODEL_MAP: dict[str, str] = {
+    "AfmoeForCausalLM": "afmoe",
+    "ApertusForCausalLM": "llama",
+    "ArceeForCausalLM": "llama",
+    "ArcticForCausalLM": "arctic",
+    "AudioFlamingo3ForConditionalGeneration": "qwen",
+    "BaiChuanForCausalLM": "baichuan",
+    "BaichuanForCausalLM": "baichuan",
+    "BailingMoeForCausalLM": "bailingmoe",
+    "BailingMoeV2ForCausalLM": "bailingmoe",
+    "BambaForCausalLM": "granite",
+    "BertForMaskedLM": "bert",
+    "BertForSequenceClassification": "bert",
+    "BertModel": "bert",
+    "BitnetForCausalLM": "bitnet",
+    "BloomForCausalLM": "bloom",
+    "BloomModel": "bloom",
+    "CamembertModel": "bert",
+    "ChameleonForCausalLM": "chameleon",
+    "ChameleonForConditionalGeneration": "chameleon",
+    "ChatGLMForConditionalGeneration": "chatglm",
+    "ChatGLMModel": "chatglm",
+    "CodeShellForCausalLM": "codeshell",
+    "CogVLMForCausalLM": "cogvlm",
+    "Cohere2ForCausalLM": "command_r",
+    "CohereForCausalLM": "command_r",
+    "DbrxForCausalLM": "dbrx",
+    "DeciLMForCausalLM": "deci",
+    "DeepseekForCausalLM": "deepseek",
+    "DeepseekV2ForCausalLM": "deepseek",
+    "DeepseekV3ForCausalLM": "deepseek",
+    "DistilBertForMaskedLM": "bert",
+    "DistilBertForSequenceClassification": "bert",
+    "DistilBertModel": "bert",
+    "Dots1ForCausalLM": "dots1",
+    "DotsOCRForCausalLM": "qwen",
+    "DreamModel": "dream",
+    "Ernie4_5ForCausalLM": "ernie",
+    "Ernie4_5_ForCausalLM": "ernie",
+    "Ernie4_5_MoeForCausalLM": "ernie",
+    "EuroBertModel": "bert",
+    "Exaone4ForCausalLM": "exaone",
+    "ExaoneForCausalLM": "exaone",
+    "ExaoneMoEForCausalLM": "exaone",
+    "FalconForCausalLM": "falcon",
+    "FalconH1ForCausalLM": "falcon_h1",
+    "FalconMambaForCausalLM": "mamba",
+    "GPT2LMHeadModel": "gpt2",
+    "GPTBigCodeForCausalLM": "starcoder",
+    "GPTNeoXForCausalLM": "gptneox",
+    "GPTRefactForCausalLM": "refact",
+    "Gemma2ForCausalLM": "gemma",
+    "Gemma3ForCausalLM": "gemma",
+    "Gemma3ForConditionalGeneration": "gemma",
+    "Gemma3TextModel": "gemma",
+    "Gemma3nForCausalLM": "gemma",
+    "Gemma3nForConditionalGeneration": "gemma",
+    "Gemma4ForConditionalGeneration": "gemma",
+    "GemmaForCausalLM": "gemma",
+    "Glm4ForCausalLM": "glm",
+    "Glm4MoeForCausalLM": "glm",
+    "Glm4MoeLiteForCausalLM": "glm",
+    "Glm4vForConditionalGeneration": "glm",
+    "Glm4vMoeForConditionalGeneration": "glm",
+    "GlmForCausalLM": "chatglm",
+    "GlmMoeDsaForCausalLM": "glm",
+    "GlmOcrForConditionalGeneration": "glm",
+    "GptOssForCausalLM": "gpt_oss",
+    "GraniteForCausalLM": "granite",
+    "GraniteMoeForCausalLM": "granite",
+    "GraniteMoeHybridForCausalLM": "granite",
+    "GraniteMoeSharedForCausalLM": "granite",
+    "GraniteSpeechForConditionalGeneration": "granite",
+    "Grok1ForCausalLM": "grok",
+    "GrokForCausalLM": "grok",
+    "GroveMoeForCausalLM": "grovemoe",
+    "HunYuanDenseV1ForCausalLM": "hunyuan",
+    "HunYuanMoEV1ForCausalLM": "hunyuan",
+    "HunYuanVLForConditionalGeneration": "hunyuan",
+    "IQuestCoderForCausalLM": "llama",
+    "InternLM2ForCausalLM": "internlm",
+    "InternLM3ForCausalLM": "internlm",
+    "JAISLMHeadModel": "jais",
+    "Jais2ForCausalLM": "jais",
+    "JambaForCausalLM": "jamba",
+    "JanusForConditionalGeneration": "januspro",
+    "JinaBertForMaskedLM": "bert",
+    "JinaBertModel": "bert",
+    "JinaEmbeddingsV5Model": "bert",
+    "KORMoForCausalLM": "qwen",
+    "KimiK25ForConditionalGeneration": "deepseek",
+    "KimiLinearForCausalLM": "kimi_linear",
+    "KimiLinearModel": "kimi_linear",
+    "KimiVLForConditionalGeneration": "deepseek",
+    "LFM2ForCausalLM": "lfm2",
+    "LLaDAMoEModel": "llada",
+    "LLaDAMoEModelLM": "llada",
+    "LLaDAModelLM": "llada",
+    "LLaMAForCausalLM": "llama",
+    "Lfm25AudioTokenizer": "lfm2",
+    "Lfm2ForCausalLM": "lfm2",
+    "Lfm2Model": "lfm2",
+    "Lfm2MoeForCausalLM": "lfm2",
+    "Llama4ForCausalLM": "llama",
+    "Llama4ForConditionalGeneration": "llama",
+    "LlamaBidirectionalModel": "llama",
+    "LlamaForCausalLM": "llama",
+    "LlamaModel": "llama",
+    "LlavaForConditionalGeneration": "llama",
+    "LlavaStableLMEpochForCausalLM": "stablelm",
+    "MPTForCausalLM": "mpt",
+    "MT5ForConditionalGeneration": "t5",
+    "MaincoderForCausalLM": "maincoder",
+    "Mamba2ForCausalLM": "mamba",
+    "MambaForCausalLM": "mamba",
+    "MambaLMHeadModel": "mamba",
+    "MiMoV2FlashForCausalLM": "mimo",
+    "MiMoV2ForCausalLM": "mimo",
+    "MiniCPM3ForCausalLM": "minicpm",
+    "MiniCPMForCausalLM": "minicpm",
+    "MiniCPMV4_6ForConditionalGeneration": "minicpm",
+    "MiniMaxM2ForCausalLM": "minimax",
+    "Ministral3ForCausalLM": "mistral3",
+    "Mistral3ForConditionalGeneration": "mistral3",
+    "MistralForCausalLM": "llama",
+    "MixtralForCausalLM": "llama",
+    "ModernBertForMaskedLM": "bert",
+    "ModernBertForSequenceClassification": "bert",
+    "ModernBertModel": "bert",
+    "NemotronForCausalLM": "nemotron",
+    "NemotronHForCausalLM": "nemotron",
+    "NeoBERT": "bert",
+    "NeoBERTForSequenceClassification": "bert",
+    "NeoBERTLMHead": "bert",
+    "NomicBertModel": "bert",
+    "OLMoForCausalLM": "olmo",
+    "Olmo2ForCausalLM": "olmo",
+    "Olmo3ForCausalLM": "olmo",
+    "OlmoForCausalLM": "olmo",
+    "OlmoeForCausalLM": "olmo",
+    "OpenELMForCausalLM": "openelm",
+    "OrionForCausalLM": "orion",
+    "PLMForCausalLM": "plm",
+    "PLaMo2ForCausalLM": "plamo",
+    "PLaMo3ForCausalLM": "plamo",
+    "PaddleOCRVLForConditionalGeneration": "ernie",
+    "PanguEmbeddedForCausalLM": "pangu",
+    "Phi3ForCausalLM": "phi",
+    "Phi4ForCausalLMV": "phi",
+    "PhiForCausalLM": "phi",
+    "PhiMoEForCausalLM": "phi",
+    "Plamo2ForCausalLM": "plamo",
+    "Plamo3ForCausalLM": "plamo",
+    "PlamoForCausalLM": "plamo",
+    "QWenLMHeadModel": "qwen",
+    "Qwen2AudioForConditionalGeneration": "qwen",
+    "Qwen2ForCausalLM": "qwen",
+    "Qwen2Model": "qwen",
+    "Qwen2MoeForCausalLM": "qwen",
+    "Qwen2VLForConditionalGeneration": "qwenvl",
+    "Qwen2VLModel": "qwenvl",
+    "Qwen2_5OmniModel": "qwenvl",
+    "Qwen2_5_VLForConditionalGeneration": "qwenvl",
+    "Qwen3ASRForConditionalGeneration": "qwen3vl",
+    "Qwen3ForCausalLM": "qwen",
+    "Qwen3Model": "qwen",
+    "Qwen3MoeForCausalLM": "qwen",
+    "Qwen3NextForCausalLM": "qwen",
+    "Qwen3OmniMoeForConditionalGeneration": "qwen3vl",
+    "Qwen3VLForConditionalGeneration": "qwen3vl",
+    "Qwen3VLMoeForConditionalGeneration": "qwen3vl",
+    "Qwen3_5ForCausalLM": "qwen",
+    "Qwen3_5ForConditionalGeneration": "qwen",
+    "Qwen3_5MoeForCausalLM": "qwen",
+    "Qwen3_5MoeForConditionalGeneration": "qwen",
+    "RND1": "qwen",
+    "RWForCausalLM": "falcon",
+    "RWKV6Qwen2ForCausalLM": "rwkv",
+    "RWKV7ForCausalLM": "rwkv",
+    "RobertaForSequenceClassification": "bert",
+    "RobertaModel": "bert",
+    "RuGPT3XLForCausalLM": "gpt2",
+    "Rwkv6ForCausalLM": "rwkv",
+    "Rwkv7ForCausalLM": "rwkv",
+    "RwkvHybridForCausalLM": "rwkv",
+    "Sarashina2VisionForCausalLM": "sarashina2",
+    "SarvamMoEForCausalLM": "bailingmoe",
+    "SeedOssForCausalLM": "olmo",
+    "SmallThinkerForCausalLM": "smallthinker",
+    "SmolLM3ForCausalLM": "llama",
+    "SolarOpenForCausalLM": "glm",
+    "StableLMEpochForCausalLM": "stablelm",
+    "StableLmForCausalLM": "stablelm",
+    "Starcoder2ForCausalLM": "starcoder",
+    "Step3p5ForCausalLM": "step3",
+    "StepVLForConditionalGeneration": "step3",
+    "T5EncoderModel": "t5",
+    "T5ForConditionalGeneration": "t5",
+    "T5WithLMHeadModel": "t5",
+    "UMT5ForConditionalGeneration": "t5",
+    "UMT5Model": "t5",
+    "UltravoxModel": "ultravox",
+    "VLlama3ForCausalLM": "llama",
+    "VoxtralForConditionalGeneration": "llama",
+    "WavTokenizerDec": "wavtokenizer",
+    "XLMRobertaForSequenceClassification": "bert",
+    "XLMRobertaModel": "bert",
+    "XverseForCausalLM": "xverse",
+    "YoutuForCausalLM": "deepseek",
+    "YoutuVLForConditionalGeneration": "deepseek",
+    "modeling_grove_moe.GroveMoeForCausalLM": "grovemoe",
+    "modeling_sarvam_moe.SarvamMoEForCausalLM": "bailingmoe",
+}
+
+
+MMPROJ_MODEL_MAP: dict[str, str] = {
+    "AudioFlamingo3ForConditionalGeneration": "ultravox",
+    "CogVLMForCausalLM": "cogvlm",
+    "DeepseekOCRForCausalLM": "deepseek",
+    "DotsOCRForCausalLM": "dotsocr",
+    "Gemma3ForConditionalGeneration": "gemma",
+    "Gemma3nForConditionalGeneration": "gemma",
+    "Gemma4ForConditionalGeneration": "gemma",
+    "Glm4vForConditionalGeneration": "qwen3vl",
+    "Glm4vMoeForConditionalGeneration": "qwen3vl",
+    "GlmOcrForConditionalGeneration": "qwen3vl",
+    "GlmasrModel": "ultravox",
+    "GraniteSpeechForConditionalGeneration": "granite",
+    "HunYuanVLForConditionalGeneration": "hunyuan",
+    "Idefics3ForConditionalGeneration": "smolvlm",
+    "InternVisionModel": "internvl",
+    "JanusForConditionalGeneration": "januspro",
+    "KimiK25ForConditionalGeneration": "kimivl",
+    "KimiVLForConditionalGeneration": "kimivl",
+    "Lfm2AudioForConditionalGeneration": "lfm2",
+    "Lfm2VlForConditionalGeneration": "lfm2",
+    "LightOnOCRForConditionalGeneration": "lighton_ocr",
+    "Llama4ForConditionalGeneration": "llama4",
+    "LlavaForConditionalGeneration": "llava",
+    "MERaLiON2ForConditionalGeneration": "ultravox",
+    "MiMoV2ForCausalLM": "mimo",
+    "MiniCPMV4_6ForConditionalGeneration": "minicpm",
+    "Mistral3ForConditionalGeneration": "llava",
+    "NemotronH_Nano_VL_V2": "nemotron",
+    "PaddleOCRVisionModel": "ernie",
+    "Phi4ForCausalLMV": "phi",
+    "Qwen2AudioForConditionalGeneration": "ultravox",
+    "Qwen2VLForConditionalGeneration": "qwenvl",
+    "Qwen2VLModel": "qwenvl",
+    "Qwen2_5OmniModel": "qwenvl",
+    "Qwen2_5_VLForConditionalGeneration": "qwenvl",
+    "Qwen3ASRForConditionalGeneration": "qwen3vl",
+    "Qwen3OmniMoeForConditionalGeneration": "qwen3vl",
+    "Qwen3VLForConditionalGeneration": "qwen3vl",
+    "Qwen3VLMoeForConditionalGeneration": "qwen3vl",
+    "Qwen3_5ForConditionalGeneration": "qwen3vl",
+    "Qwen3_5MoeForConditionalGeneration": "qwen3vl",
+    "RADIOModel": "nemotron",
+    "Sarashina2VisionForCausalLM": "sarashina2",
+    "SmolVLMForConditionalGeneration": "smolvlm",
+    "StepVLForConditionalGeneration": "step3",
+    "UltravoxModel": "ultravox",
+    "VoxtralForConditionalGeneration": "ultravox",
+    "YoutuVLForConditionalGeneration": "youtuvl",
+}
+
+
+_TEXT_MODEL_MODULES = sorted(set(TEXT_MODEL_MAP.values()))
+_MMPROJ_MODEL_MODULES = sorted(set(MMPROJ_MODEL_MAP.values()))
+
+
+_loaded_text_modules: set[str] = set()
+_loaded_mmproj_modules: set[str] = set()
+
+
+def load_all_models() -> None:
+    """Import all model modules to trigger @ModelBase.register() decorators."""
+    if len(_loaded_text_modules) != len(_TEXT_MODEL_MODULES):
+        for module_name in _TEXT_MODEL_MODULES:
+            if module_name not in _loaded_text_modules:
+                try:
+                    __import__(f"conversion.{module_name}")
+                    _loaded_text_modules.add(module_name)
+                except Exception as e:
+                    logger.warning(f"Failed to load model module {module_name}: {e}")
+
+    if len(_loaded_mmproj_modules) != len(_MMPROJ_MODEL_MODULES):
+        for module_name in _MMPROJ_MODEL_MODULES:
+            if module_name not in _loaded_mmproj_modules:
+                try:
+                    __import__(f"conversion.{module_name}")
+                    _loaded_mmproj_modules.add(module_name)
+                except Exception as e:
+                    logger.warning(f"Failed to load model module {module_name}: {e}")
+
+
+def get_model_class(name: str, mmproj: bool = False) -> Type[ModelBase]:
+    """Dynamically import and return a model class by its HuggingFace architecture name."""
+    relevant_map = MMPROJ_MODEL_MAP if mmproj else TEXT_MODEL_MAP
+    if name not in relevant_map:
+        raise NotImplementedError(f"Architecture {name!r} not supported!")
+    module_name = relevant_map[name]
+    __import__(f"conversion.{module_name}")
+    model_type = ModelType.MMPROJ if mmproj else ModelType.TEXT
+    return ModelBase._model_classes[model_type][name]
+
+
+def print_registered_models() -> None:
+    load_all_models()
+    logger.error("TEXT models:")
+    for name in sorted(TEXT_MODEL_MAP.keys()):
+        logger.error(f"  - {name}")
+    logger.error("MMPROJ models:")
+    for name in sorted(MMPROJ_MODEL_MAP.keys()):
+        logger.error(f"  - {name}")

conversion/afmoe.py

@@ -0,0 +1,79 @@
+from __future__ import annotations
+
+from typing import Callable, Iterable, TYPE_CHECKING
+
+import torch
+
+if TYPE_CHECKING:
+    from torch import Tensor
+
+from .base import ModelBase, gguf
+
+from .llama import LlamaModel
+
+
+@ModelBase.register("AfmoeForCausalLM")
+class AfmoeModel(LlamaModel):
+    model_arch = gguf.MODEL_ARCH.AFMOE
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+
+        # MoE parameters
+        if (n_shared_experts := self.hparams.get("num_shared_experts")) is not None:
+            self.gguf_writer.add_expert_shared_count(n_shared_experts)
+        if (moe_intermediate_size := self.hparams.get("moe_intermediate_size")) is not None:
+            self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
+        if (n_dense_layers := self.hparams.get("num_dense_layers")) is not None:
+            self.gguf_writer.add_leading_dense_block_count(n_dense_layers)
+
+        # Route normalization and scaling
+        if (route_norm := self.hparams.get("route_norm")) is not None:
+            self.gguf_writer.add_expert_weights_norm(route_norm)
+        if (route_scale := self.hparams.get("route_scale")) is not None:
+            self.gguf_writer.add_expert_weights_scale(route_scale)
+
+        # Sliding window attention
+        if (sliding_window := self.hparams.get("sliding_window")) is not None:
+            self.gguf_writer.add_sliding_window(sliding_window)
+
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        name, gen = item
+
+        if name.endswith(".expert_bias"):
+            name = name.replace(".expert_bias", ".expert_bias.bias")
+
+        return super().filter_tensors((name, gen))
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        # Handle expert weights - they're already merged in the HF format
+        # process the experts separately
+        if name.find("mlp.experts") != -1:
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
+            assert bid is not None
+
+            if self._experts is None:
+                self._experts = [{} for _ in range(self.block_count)]
+
+            self._experts[bid][name] = data_torch
+
+            if len(self._experts[bid]) >= n_experts * 3:
+                # merge the experts into a single 3d tensor
+                for w_name in ["gate_proj", "up_proj", "down_proj"]:
+                    datas: list[Tensor] = []
+
+                    for xid in range(n_experts):
+                        ename_to_retrieve = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight"
+                        datas.append(self._experts[bid][ename_to_retrieve])
+                        del self._experts[bid][ename_to_retrieve]
+
+                    data_torch = torch.stack(datas, dim=0)
+                    merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight"
+                    yield from ModelBase.modify_tensors(self, data_torch, merged_name, bid)
+
+                return
+            else:
+                return
+
+        yield from ModelBase.modify_tensors(self, data_torch, name, bid)

conversion/arctic.py

@@ -0,0 +1,162 @@
+from __future__ import annotations
+
+import json
+import sys
+
+from typing import Iterable, TYPE_CHECKING
+
+import torch
+
+if TYPE_CHECKING:
+    from torch import Tensor
+
+from .base import ModelBase, SentencePieceTokenTypes, TextModel, gguf, logger
+
+from .llama import LlamaModel
+
+
+@ModelBase.register("ArcticForCausalLM")
+class ArcticModel(TextModel):
+    model_arch = gguf.MODEL_ARCH.ARCTIC
+
+    def set_vocab(self):
+        # The reason for using a custom implementation here is that the
+        # snowflake-arctic-instruct model redefined tokens 31998 and 31999 from
+        # tokenizer.model and used them as BOS and EOS instead of adding new tokens.
+        from sentencepiece import SentencePieceProcessor
+
+        tokenizer_path = self.dir_model / 'tokenizer.model'
+
+        if not tokenizer_path.is_file():
+            logger.error(f'Error: Missing {tokenizer_path}')
+            sys.exit(1)
+
+        # Read the whole vocabulary from the tokenizer.model file
+        tokenizer = SentencePieceProcessor()
+        tokenizer.LoadFromFile(str(tokenizer_path))
+
+        vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size())
+
+        tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
+        scores: list[float] = [-10000.0] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNUSED] * vocab_size
+
+        for token_id in range(tokenizer.vocab_size()):
+
+            piece = tokenizer.IdToPiece(token_id)
+            text = piece.encode("utf-8")
+            score = tokenizer.GetScore(token_id)
+
+            toktype = SentencePieceTokenTypes.NORMAL
+            if tokenizer.IsUnknown(token_id):
+                toktype = SentencePieceTokenTypes.UNKNOWN
+            elif tokenizer.IsControl(token_id):
+                toktype = SentencePieceTokenTypes.CONTROL
+            elif tokenizer.IsUnused(token_id):
+                toktype = SentencePieceTokenTypes.UNUSED
+            elif tokenizer.IsByte(token_id):
+                toktype = SentencePieceTokenTypes.BYTE
+
+            tokens[token_id] = text
+            scores[token_id] = score
+            toktypes[token_id] = toktype
+
+        # Use the added_tokens_decoder field from tokeniser_config.json as the source
+        # of information about added/redefined tokens and modify them accordingly.
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+
+                if "added_tokens_decoder" in tokenizer_config_json:
+                    added_tokens_decoder = tokenizer_config_json["added_tokens_decoder"]
+                    for token_id, token_json in added_tokens_decoder.items():
+                        token_id = int(token_id)
+                        if token_id >= vocab_size:
+                            logger.debug(f'ignore token {token_id}: id is out of range, max={vocab_size - 1}')
+                            continue
+
+                        token_content = token_json["content"]
+                        token_type = SentencePieceTokenTypes.USER_DEFINED
+                        token_score = -10000.0
+
+                        # Map unk_token to UNKNOWN, other special tokens to CONTROL
+                        # Set the score to 0.0 as in the original tokenizer.model
+                        if ("special" in token_json) and token_json["special"]:
+                            if token_content == tokenizer_config_json["unk_token"]:
+                                token_type = SentencePieceTokenTypes.UNKNOWN
+                            else:
+                                token_type = SentencePieceTokenTypes.CONTROL
+                            token_score = 0.0
+
+                        logger.info(f"Setting added token {token_id} to '{token_content}' (type: {token_type}, score: {token_score:.2f})")
+                        tokens[token_id] = token_content.encode("utf-8")
+                        toktypes[token_id] = token_type
+                        scores[token_id] = token_score
+
+        self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_scores(scores)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
+        special_vocab.add_to_gguf(self.gguf_writer)
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        self.gguf_writer.add_vocab_size(hparams["vocab_size"])
+        self.gguf_writer.add_rope_dimension_count(hparams["hidden_size"] // hparams["num_attention_heads"])
+
+    _experts: list[dict[str, Tensor]] | None = None
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        n_head = self.hparams["num_attention_heads"]
+        n_kv_head = self.hparams.get("num_key_value_heads")
+
+        if name.endswith("q_proj.weight"):
+            data_torch = LlamaModel.permute(data_torch, n_head, n_head)
+        if name.endswith("k_proj.weight"):
+            data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head)
+
+        # process the experts separately
+        if name.find("block_sparse_moe.experts") != -1:
+            n_experts = self.hparams["num_local_experts"]
+
+            assert bid is not None
+
+            if self._experts is None:
+                self._experts = [{} for _ in range(self.block_count)]
+
+            self._experts[bid][name] = data_torch
+
+            if len(self._experts[bid]) >= n_experts * 3:
+                # merge the experts into a single 3d tensor
+                for wid in ["w1", "w2", "w3"]:
+                    datas: list[Tensor] = []
+
+                    for xid in range(n_experts):
+                        ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.{wid}.weight"
+                        datas.append(self._experts[bid][ename])
+                        del self._experts[bid][ename]
+
+                    data_torch = torch.stack(datas, dim=0)
+
+                    merged_name = f"layers.{bid}.feed_forward.experts.{wid}.weight"
+
+                    yield from super().modify_tensors(data_torch, merged_name, bid)
+                return
+            else:
+                return
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
+    def prepare_tensors(self):
+        super().prepare_tensors()
+
+        if self._experts is not None:
+            # flatten `list[dict[str, Tensor]]` into `list[str]`
+            experts = [k for d in self._experts for k in d.keys()]
+            if len(experts) > 0:
+                raise ValueError(f"Unprocessed experts: {experts}")

conversion/baichuan.py

@@ -0,0 +1,59 @@
+from __future__ import annotations
+
+from typing import Iterable, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from torch import Tensor
+
+from .base import ModelBase, TextModel, gguf, logger
+
+
+@ModelBase.register("BaichuanForCausalLM", "BaiChuanForCausalLM")
+class BaichuanModel(TextModel):
+    model_arch = gguf.MODEL_ARCH.BAICHUAN
+
+    def set_vocab(self):
+        self._set_vocab_sentencepiece()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+
+        self.gguf_writer.add_tensor_data_layout("Meta AI original pth")
+        self.gguf_writer.add_rope_dimension_count(self.hparams["hidden_size"] // self.hparams["num_attention_heads"])
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        head_count = self.hparams["num_attention_heads"]
+        head_count_kv = self.hparams.get("num_key_value_heads", head_count)
+
+        if bid is not None and name == f"model.layers.{bid}.self_attn.W_pack.weight":
+            logger.info(f"Unpacking and permuting layer {bid}")
+            yield from [
+                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid),
+                    self._reverse_hf_permute_part(data_torch, 0, head_count, head_count)),
+                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid),
+                    self._reverse_hf_permute_part(data_torch, 1, head_count, head_count_kv)),
+                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid),
+                    self._reverse_hf_part(data_torch, 2)),
+            ]
+        else:
+            yield from self.modify_tensors(data_torch, self.map_tensor_name(name), bid)
+
+    def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor:
+        if n_kv_head is not None and n_head != n_kv_head:
+            n_head //= n_kv_head
+
+        return (
+            weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])
+            .swapaxes(1, 2)
+            .reshape(weights.shape)
+        )
+
+    def _reverse_hf_permute_part(
+        self, weights: Tensor, n_part: int, n_head: int, n_head_kv: int | None = None,
+    ) -> Tensor:
+        r = weights.shape[0] // 3
+        return self._reverse_hf_permute(weights[r * n_part:r * n_part + r, ...], n_head, n_head_kv)
+
+    def _reverse_hf_part(self, weights: Tensor, n_part: int) -> Tensor:
+        r = weights.shape[0] // 3
+        return weights[r * n_part:r * n_part + r, ...]

conversion/bailingmoe.py

@@ -0,0 +1,216 @@
+from __future__ import annotations
+
+from typing import Callable, Iterable, TYPE_CHECKING
+
+import torch
+
+if TYPE_CHECKING:
+    from torch import Tensor
+
+from .base import ModelBase, TextModel, gguf
+
+
+@ModelBase.register("BailingMoeForCausalLM")
+class BailingMoeModel(TextModel):
+    model_arch = gguf.MODEL_ARCH.BAILINGMOE
+
+    def set_vocab(self):
+        self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        if (rope_dim := hparams.get("head_dim")) is None:
+            rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
+
+        self.gguf_writer.add_rope_dimension_count(rope_dim)
+        self.gguf_writer.add_leading_dense_block_count(hparams["first_k_dense_replace"])
+        self.gguf_writer.add_vocab_size(hparams["vocab_size"])
+        self.gguf_writer.add_expert_feed_forward_length(hparams["moe_intermediate_size"])
+        self.gguf_writer.add_expert_weights_scale(1.0)
+        self.gguf_writer.add_expert_shared_count(hparams["num_shared_experts"])
+        self.gguf_writer.add_expert_weights_norm(hparams["norm_topk_prob"])
+
+    _experts: list[dict[str, Tensor]] | None = None
+
+    @staticmethod
+    def permute(weights: Tensor, n_head: int, n_head_kv: int | None):
+        if n_head_kv is not None and n_head != n_head_kv:
+            n_head = n_head_kv
+        return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])
+                .swapaxes(1, 2)
+                .reshape(weights.shape))
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        n_head = self.hparams["num_attention_heads"]
+        n_kv_head = self.hparams.get("num_key_value_heads")
+        n_embd = self.hparams["hidden_size"]
+        if (head_dim := self.hparams.get("head_dim")) is None:
+            head_dim = n_embd // n_head
+
+        output_name = self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT)
+
+        if name.endswith("attention.dense.weight"):
+            yield from super().modify_tensors(data_torch, self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_OUT, bid), bid)
+            return
+        elif name.endswith("query_key_value.weight"):
+            q, k, v = data_torch.split([n_head * head_dim, n_kv_head * head_dim, n_kv_head * head_dim], dim=-2)
+
+            yield from super().modify_tensors(BailingMoeModel.permute(q, n_head, n_head), self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid), bid)
+            yield from super().modify_tensors(BailingMoeModel.permute(k, n_head, n_kv_head), self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid), bid)
+            yield from super().modify_tensors(v,self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid), bid)
+            return
+        elif name.find("mlp.experts") != -1:
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
+            assert bid is not None
+
+            if self._experts is None:
+                self._experts = [{} for _ in range(self.block_count)]
+
+            self._experts[bid][name] = data_torch
+
+            if len(self._experts[bid]) >= n_experts * 3:
+                # merge the experts into a single 3d tensor
+                for w_name in ["down_proj", "gate_proj", "up_proj"]:
+                    datas: list[Tensor] = []
+
+                    for xid in range(n_experts):
+                        ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight"
+                        datas.append(self._experts[bid][ename])
+                        del self._experts[bid][ename]
+
+                    data_torch = torch.stack(datas, dim=0)
+
+                    merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight"
+
+                    new_name = self.map_tensor_name(merged_name)
+
+                    yield from super().modify_tensors(data_torch, new_name, bid)
+
+            return
+
+        new_name = self.map_tensor_name(name)
+
+        if new_name == output_name and self.hparams.get("norm_head"):
+            data_torch = data_torch.float()
+            data_torch /= torch.norm(data_torch, p=2, dim=0, keepdim=True) + 1e-7
+
+        yield from super().modify_tensors(data_torch, new_name, bid)
+
+    def prepare_tensors(self):
+        super().prepare_tensors()
+
+        if self._experts is not None:
+            # flatten `list[dict[str, Tensor]]` into `list[str]`
+            experts = [k for d in self._experts for k in d.keys()]
+            if len(experts) > 0:
+                raise ValueError(f"Unprocessed experts: {experts}")
+
+
+@ModelBase.register("BailingMoeV2ForCausalLM")
+class BailingMoeV2Model(TextModel):
+    model_arch = gguf.MODEL_ARCH.BAILINGMOE2
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if nextn_layers := self.hparams.get("num_nextn_predict_layers", 0):
+            self.block_count = self.hparams["num_hidden_layers"] + nextn_layers
+            self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
+
+    def set_vocab(self):
+        self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        if (rope_dim := hparams.get("head_dim")) is None:
+            rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
+
+        self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5)))
+        self.gguf_writer.add_leading_dense_block_count(hparams["first_k_dense_replace"])
+        self.gguf_writer.add_vocab_size(hparams["vocab_size"])
+        self.gguf_writer.add_expert_feed_forward_length(hparams["moe_intermediate_size"])
+        self.gguf_writer.add_expert_shared_feed_forward_length(hparams.get("moe_shared_expert_intermediate_size", hparams["moe_intermediate_size"] * hparams["num_shared_experts"]))
+        self.gguf_writer.add_expert_weights_scale(hparams["routed_scaling_factor"])
+        self.gguf_writer.add_expert_shared_count(hparams["num_shared_experts"])
+        self.gguf_writer.add_expert_weights_norm(hparams["norm_topk_prob"])
+
+        if (nextn_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
+            self.gguf_writer.add_nextn_predict_layers(nextn_layers)
+
+    _experts: list[dict[str, Tensor]] | None = None
+
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        name, gen = item
+
+        if name.endswith(".expert_bias"):
+            name = name.replace(".expert_bias", ".expert_bias.bias")
+
+        return super().filter_tensors((name, gen))
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        if "mlp.experts" in name:
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
+            assert bid is not None
+
+            if self._experts is None:
+                self._experts = [{} for _ in range(self.block_count)]
+
+            self._experts[bid][name] = data_torch
+
+            if len(self._experts[bid]) >= n_experts * 3:
+                # merge the experts into a single 3d tensor
+                for w_name in ["down_proj", "gate_proj", "up_proj"]:
+                    datas: list[Tensor] = []
+
+                    for xid in range(n_experts):
+                        ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight"
+                        datas.append(self._experts[bid][ename])
+                        del self._experts[bid][ename]
+
+                    data_torch = torch.stack(datas, dim=0)
+
+                    merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight"
+
+                    yield from super().modify_tensors(data_torch, merged_name, bid)
+            return
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
+    def prepare_tensors(self):
+        super().prepare_tensors()
+
+        if self._experts is not None:
+            # flatten `list[dict[str, Tensor]]` into `list[str]`
+            experts = [k for d in self._experts for k in d.keys()]
+            if len(experts) > 0:
+                raise ValueError(f"Unprocessed experts: {experts}")
+
+
+@ModelBase.register("SarvamMoEForCausalLM", "modeling_sarvam_moe.SarvamMoEForCausalLM")
+class SarvamMoEModel(BailingMoeV2Model):
+    model_arch = gguf.MODEL_ARCH.BAILINGMOE2
+    # Sarvam-MoE shares the BailingMoeV2 architecture; only differences:
+    #  - full rotary (no partial_rotary_factor)
+    #  - expert bias is zero-mean normalized at load time
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        if (rope_dim := hparams.get("head_dim")) is None:
+            rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
+        # Override the partial-rotary value written by BailingMoeV2 with the full rotary dim
+        self.gguf_writer.add_rope_dimension_count(rope_dim)
+
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        name, gen = item
+        if name.endswith(".expert_bias"):
+            # Sarvam normalizes expert bias to zero mean
+            inner = gen
+
+            def gen():
+                t = inner()
+                return t - t.mean()
+        return super().filter_tensors((name, gen))