This commit removes the precompiled headers that I added in Commit
3bcfeb700 ("cmake : add PCH and unity build to improve build times
(#28091)").
The motivation for this is that this looked good when developing this
but has caused multiple issues that I had taken into consideration and
we have decided to remove it and only keep the unity builds from the
above commit.
Refs: https://github.com/ggml-org/llama.cpp/pull/28882#issuecomment-5662272126
This commit moves the llama_n_rs_seq function call to before the
llama_decode call and returns directly if the check is true, removing
the setting of res and the goto statement.
The motivation for this change is to avoid the llama_decode call if it
is not needed.
* scripts : add initial profiling script (wip)
* src : add precompile headers (PCH) for models.h
* common : add common.h as PCH
* ggml : add PCH for ggml-impl.h
* mtmd : use PCH for models.h
* scripts : add script to build with Server/Tools/Tests
* server : add PCH for common.h
* docs: add profiling progress notes (wip)
* ggml : add exclude for GCC + SVE on ARM
Refs: https://github.com/ggml-org/llama.cpp/actions/runs/33393906061/job/99493756214?pr=28091
* ggml : attempt to fix use of std::hardware_destructive_inference_size
Refs: https://github.com/ggml-org/llama.cpp/actions/runs/33396221677/job/99501265689?pr=28091
* squash! ggml : attempt to fix use of std::hardware_destructive_inference_size
Add a version check for GCC 12 to conditionally apply the `-Winterference-size`
pragma.
* editorconfig : exclude profiling reports dir
This directory will not be included in the merge later and this commit
can be ignore at that point. Just fixing to keep CI happy.
* ggml : skip PCH for gcc on non-x86 architectures
* tests : add PCH for peg-parser/tests.h
There are 7 peg-parser tests that can share one PCH instead of then each
parsing the full tests.h.
* common : add PCH for chat.h
* docs : update linux build profiling full results
Just updating after a number of PCH additions. These are not exact
figures and will vary a bit from run to run, but they give a general idea
of the performance impact of PCH.
* cmake : introduce unity build for models
This commit introduces a unity build for the models to improve
compilation time.
The improvements were roughly the following:
```console
+------------------------+-----+------------+------------+------------+
| Build | TUs | Frontend | Backend | Total |
+------------------------+-----+------------+------------+------------+
| Full, master | 396 | 811.0 s | 692.2 s | 1,503.2 s |
| Full, with PCH | 405 | 380.0 s | 664.7 s | 1,044.7 s |
| Full, with PCH + UB | 264 | 357.7 s | 635.7 s | 993.4 s |
+------------------------+-----+------------+------------+------------+
TU = Translation Unit.
Full = includes Server, Tools, and Tests.
PCH = precompiled headers.
UB = unity build for models.
```
* docs : update linux profiling table with unitiy build results
* docs : update mac profiling results to include unity build [no ci]
* docs: remove profiling reports
* scripts : merge build profile scripts into one script
I was lazy before and just copied the first script to enable Tests,
Server, and Tools. This now merges them into a single script.
* Revert "editorconfig : exclude profiling reports dir" [no ci]
This reverts commit 2922a12118a0730d2f7632bcba265b44a0856c59.
* src : rename ggml_view_2d_slice to gemma3n_view_2d_slice
This is to be consistent with the rename in gemma4.cpp which was
required to avoid a name clash.
* cmake : add build profile script for windows [no ci]
This commit adds a port of the scripts/build-profile.sh script to
windows powershell.
This was developed on Windows on ARM but should work on X64 as well but
needs to be tested there as well.
* server: fix speculation after an image
Pass the actual position to the drafter after an image, instead of the
token count. Affects every drafter, not just DFlash.
* rename draft n_past to pos0
n_past is used to denote number of tokens and this parameter is meant to be a position
* speculative: fix failed to decode mtmd chunk with DFlash
When using DFlash w/ vision models, the drafter memory fails to
allocate new tokens because images report a fixed offset. Stop copying
them to allow the drafter to continue.
* address PR feedback
limit M-RoPE skip to images only, allow audio to pass through. Clean up
comments to align to the updated implementation
Templates that default an optional variable to none and then test its
membership in a map hit an error, while the same expression is a normal
lookup returning false in Jinja. The undefined counterpart of this case
was already handled just above.
* chat : split specialized parsers into common/parsers
Move the 14 dedicated template parsers out of chat.cpp into one file each under
common/parsers, mirroring the src/models split. chat.cpp keeps the template
detection in common_chat_try_specialized_template() and drops from 3915 to 1513
lines.
common/parsers/parsers.h holds the shared helpers and one declaration per
parser. foreach_function/foreach_parameter become inline there since nothing in
chat.cpp uses them any more; common_chat_template_direct_apply_impl and
common_chat_template_generation_prompt_impl lose static and carry their default
arguments in the header. Parser-specific helpers move with their parser:
is_lfm2_template, deepseek_v4_sort_tool_results and the gemma4 turn builder.
No functional change.
Assisted-by: Claude Opus 5
* chat : enumerate parser sources instead of globbing
file(GLOB) does not re-run CMake when a source file is added or removed, so an
incremental build silently keeps building the old set. List the parsers in
common/parsers/sources.cmake and include it from common/CMakeLists.txt.
Assisted-by: Claude Opus 5
* split helpers, add newlines
Let llama_print_build_info write to a caller-provided FILE* instead of
hardcoding stderr. The parameter defaults to stderr so existing callers
keep their current behavior.
The version command in llama-app now passes stdout, so plain version
output goes to stdout where users expect it.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* common, server : enable preserve_reasoning kwarg by default, log its effective state
If the preserve_reasoning chat template kwarg is not specified explicitly
via --reasoning-preserve / --no-reasoning-preserve, it is enabled by
default after argument processing. The server logs the effective state of
the kwarg, warns that it is enabled by default when the template supports
it, and only warns "has no effect" when it was enabled explicitly on a
template that does not support it. Setting the kwarg via
--chat-template-kwargs is deprecated.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : update comment
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
---------
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
* dflash : fuse the encoder into the KV injection decode
The encoder is a single fc + norm, but running it as a separate
llama_encode forced a device-to-host round trip of its output before the
injection decode could re-upload it, plus a second graph build per
round. Fold the encoder into the decoder's embd branch and feed the
target features directly to one llama_decode.
Assisted-by: Claude Fable
* nit
* Apply batched suggestions from code review
Co-authored-by: Ruixiang Wang <wangruixiang07@outlook.com>
* Fix missing references from renaming
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Ruixiang Wang <wangruixiang07@outlook.com>
Rename the --tensor-read-lazy CLI argument to --lazy-mode, to match the
internal lazy_mode parameter, and add a -lzm shorthand. Sync the READMEs.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* Add ctx-per-slot argument for unifid KV cache
* Swap out ctx fractions for ctx pool slots
* Formatting cleanup
* Remove ctx-pool-slots, make ctx-per-slot an int
* refactor it
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* spec : add DFlash2 support (local convolution + candidate selector) (#27342)
* support DFlash2
* Add p_min in DFlash2
Assisted-by: Claude Opus 5
* Revert unnecessary changes
Assisted-by: Claude Opus 5
* Revert draft sampling in rejection sampling
Assisted-by: Claude Opus 5
* Refactor code structure
Assisted-by: Claude Opus 5
* Delete embedding scaling
Assisted-by: Claude Opus 5
* Gate output transforms on DFlash2
Assisted-by: Claude Opus 5
* Optimize Dflash 2 cost
Assisted-by: Claude Opus 5
* Avoid using atoi
Assisted-by: Claude Opus 5
* Modify comments
Assisted-by: Claude Opus 5
* Move llama_model_dflash_selector_top_k to llama-ext.h
Assisted-by: Claude Opus 5
* Formatting
Assisted-by: Claude Opus 5
* Apply patch to fix the mrope bug
Assisted-by: Claude Opus 5
* fix ci
Assisted-by: Claude Opus 5
* Fix graph number calculation
Assisted-by: Claude Opus 5
* rename hid and unary
Assisted-by: Claude Opus 5
---------
Co-authored-by: Jian Chen <jianchen0311@gmail.com>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
* revert top-k.cu changes
---------
Co-authored-by: Zihan Zhang <tiancaizhangdaxian@sjtu.edu.cn>
Co-authored-by: Jian Chen <jianchen0311@gmail.com>
* Add benchmark-only synthetic speculative acceptance to llama-server and llama-cli
* Address review comments
* Address review comments
* Add some comments in the code
* common : dedupe --n-cpu-moe / --spec-draft-n-cpu-moe override loops
* common : add --n-cpu-ffn to CPU-offload dense FFN weights of first N layers
* common : generalize llm_ffn_block_regex over the FFN regex, drop TODO
The device_info loop iterates over the discovered devices and gets
the available and total memory counts. With the CUDA backend (and
possibly others too) this requires creating a GPU context, which,
in case of CUDA, results in a 550 MB VRAM allocation.
For this information to be used in any way, the log verbosity must
be set to LOG_LEVEL_TRACE. If it's not, including in the default
configuration, the contexts get created, memory sizes get queried,
then the log function quietly discards the data.
In certain cases the user may not want to use any GPU resources.
The device_loop iteration is the only place touching the GPU that
cannot be skipped.
Fix by checking the verbosity level and skipping the loop if there
would be no output.
Concedo
Daniel Bevenius
Aldehir Rojas
Xuan-Son Nguyen
Sigbjørn Skjæret
Jesus Gulfo
Aaron Teo
Pascal
Aman Gupta
Piotr Wilkin (ilintar)
Adrien Gallouët
Sergey Sklyarov
Georgi Gerganov
王金旭
Ruixiang Wang
Bartowski
Gaurav Garg
Jonas J
Bartosz Taudul