model: add Hy3 (hy_v3) support with MTP speculative decoding (#25395)

* model: add Hy3 (hy_v3) architecture support

Adds Tencent Hunyuan 3 (HF architecture HYV3ForCausalLM, GGUF arch
hy_v3): a MoE decoder stack with per-head Q/K RMSNorm, a sigmoid
router with expert selection bias, an always-active ungated shared
expert, and leading dense block(s) (first_k_dense_replace).

The base implementation is ported from charlie12345's fork
(https://github.com/charlie12345/ROCmFPX, src/models/hyv3.cpp),
adapted to current mainline APIs (hparams.n_layer(), build_qkv,
build_moe_ffn with fused gate_up + scale tensors, output_s).

Note: blk.N.exp_probs_b is stored without a .bias suffix for
compatibility with existing hy_v3 GGUFs produced by that fork.

Co-Authored-By: charlie12345 <charlie12345@users.noreply.github.com>
Co-authored-by: Piotr Wilkin <ilintar@gmail.com>
Assisted-by: Claude Fable 5

README.md

@@ -8,7 +8,7 @@
 [![Docker](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml)
 [![Winget](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml)
 
-[Manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md)
+[Manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md) / [maintainer PRs](https://github.com/ggml-org/llama.cpp/issues?q=is%3Apr%20is%3Aopen%20draft%3AFalse%20(author%3Argerganov%20OR%20author%3AKitaitiMakoto%20OR%20author%3Adanbev%20OR%20author%3Aaldehir%20OR%20author%3Amax-krasnyansky%20OR%20author%3ACISC%20OR%20author%3Aggerganov%20OR%20author%3Aam17an%20OR%20author%3Abartowski1182%20OR%20author%3Ahipudding%20OR%20author%3AServeurpersoCom%20OR%20author%3Apwilkin%20OR%20author%3Areeselevine%20OR%20author%3Angxson%20OR%20author%3Ajeffbolznv%20OR%20author%3A0cc4m%20OR%20author%3Aangt%20OR%20author%3AIMbackK%20OR%20author%3Aarthw%20OR%20author%3AJohannesGaessler%20OR%20author%3AORippler%20OR%20author%3Aruixiang63%20OR%20author%3Axctan%20OR%20author%3Aallozaur%20OR%20author%3Ayomaytk%20OR%20author%3Aaendk%20OR%20author%3Agaugarg-nv%20OR%20author%3Ataronaeo%20OR%20author%3Aforforever73%20OR%20author%3Alhez%20OR%20author%3Anetrunnereve%20OR%20author%3Afairydreaming)%20sort%3Aupdated-desc)
 
 LLM inference in C/C++
 

common/chat-auto-parser-generator.cpp

@@ -262,6 +262,10 @@ common_peg_parser analyze_tools::build_func_parser(common_chat_peg_builder & p,
     bool              matched_atomic = false;
     common_peg_parser func_parser    = p.eps();
 
+    if (!function.args_separator.empty()) {
+        open = open + p.space() + p.literal(function.args_separator);
+    }
+
     if (!function.name_suffix.empty()) {
         func_parser    = open + call_id_section + p.space() + args;
         matched_atomic = true;

common/chat-auto-parser.h

@@ -192,9 +192,10 @@ struct tool_format_analysis {
 };
 
 struct tool_function_analysis {
-    std::string name_prefix;  // e.g., "<function=", "\"name\": \"", "functions."
-    std::string name_suffix;  // e.g., ">", "\"", ":0"
-    std::string close;        // e.g., "</function>", "" (for tag-based)
+    std::string name_prefix;     // e.g., "<function=", "\"name\": \"", "functions."
+    std::string name_suffix;     // e.g., ">", "\"", ":0"
+    std::string args_separator;  // e.g., "<tool_sep>" (marker between function name and arguments)
+    std::string close;           // e.g., "</function>", "" (for tag-based)
 };
 
 struct tool_arguments_analysis {

common/chat-diff-analyzer.cpp

@@ -259,6 +259,7 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
     LOG_DBG("per_call_end: '%s'\n", tools.format.per_call_end.c_str());
     LOG_DBG("func_name_prefix: '%s'\n", tools.function.name_prefix.c_str());
     LOG_DBG("func_name_suffix: '%s'\n", tools.function.name_suffix.c_str());
+    LOG_DBG("func_args_separator: '%s'\n", tools.function.args_separator.c_str());
     LOG_DBG("func_close: '%s'\n", tools.function.close.c_str());
     LOG_DBG("call_id_prefix: '%s'\n", tools.call_id.prefix.c_str());
     LOG_DBG("call_id_suffix: '%s'\n", tools.call_id.suffix.c_str());
@@ -302,6 +303,7 @@ void autoparser::collect_preserved_tokens() {
     add_token(tools.format.per_call_end);
     add_token(tools.function.name_prefix);
     add_token(tools.function.name_suffix);
+    add_token(tools.function.args_separator);
     add_token(tools.function.close);
     add_token(tools.arguments.start);
     add_token(tools.arguments.end);
@@ -1051,6 +1053,23 @@ void analyze_tools::check_per_call_markers() {
         format.section_start.clear();
         format.section_end.clear();
     }
+
+    if (!format.per_call_end.empty()) {
+        auto count_occurrences = [](const std::string & haystack, const std::string & needle) {
+            size_t count = 0;
+            for (size_t pos = haystack.find(needle); pos != std::string::npos;
+                 pos = haystack.find(needle, pos + needle.size())) {
+                count++;
+            }
+            return count;
+        };
+        size_t calls_one = count_occurrences(one_vs_two->output_A, format.per_call_end);
+        size_t calls_two = count_occurrences(one_vs_two->output_B, format.per_call_end);
+        if (calls_one > 0 && calls_one == calls_two) {
+            format.section_end = format.per_call_end;
+            format.per_call_end.clear();
+        }
+    }
 }
 
 void analyze_tools::extract_function_markers() {
@@ -1132,6 +1151,17 @@ void analyze_tools::extract_function_markers() {
             auto suf_result = suffix_parser.parse_and_extract(diff.suffix);
             if (suf_result.result.success()) {
                 function.name_suffix += suf_result.tags["ext"];
+
+                auto arg_start = [&](common_peg_parser_builder &p) {
+                    return p.marker() + p.space() + p.choice({ p.literal(ARG_FIRST), p.literal(ARG_SECOND) });
+                };
+                auto sep_parser = build_tagged_peg_parser([&](common_peg_parser_builder &p) {
+                    return p.tag("sep", p.zero_or_more(p.negate(arg_start(p)) + p.any())) + arg_start(p);
+                });
+                auto sep_result = sep_parser.parse_and_extract(diff.suffix.substr(suf_result.tags["ext"].size()));
+                if (sep_result.result.success()) {
+                    function.args_separator = trim_whitespace(sep_result.tags["sep"]);
+                }
             }
         }
 

common/jinja/value.cpp

@@ -750,11 +750,50 @@ const func_builtins & value_string_t::get_builtins() const {
             res->val_str.mark_input_based_on(args.get_pos(0)->val_str);
             return res;
         }},
+        {"format", [](const func_args & args) -> value {
+            value val_input = args.get_pos(0);
+            if (!is_val<value_string>(val_input)) {
+                throw raised_exception("format() first argument must be a string");
+            }
+            const jinja::string & fmt = val_input->as_string();
+            const bool fmt_is_input = fmt.all_parts_are_input();
+
+            const std::string str = fmt.str();
+            jinja::string result;
+            std::string literal;
+            auto flush_literal = [&]() {
+                if (!literal.empty()) {
+                    result.parts.push_back({fmt_is_input, literal});
+                    literal.clear();
+                }
+            };
+
+            size_t arg_idx = 1; // positional args follow the format string
+            for (size_t i = 0; i < str.size(); ++i) {
+                if (str[i] != '{') {
+                    literal += str[i];
+                    continue;
+                }
+                if (i + 1 >= str.size() || str[i + 1] != '}') {
+                    throw not_implemented_exception("format() only supports simple '{}' placeholders");
+                }
+                ++i;
+                flush_literal();
+                const jinja::string arg_str = args.get_pos(arg_idx++)->as_string();
+                result.parts.insert(result.parts.end(), arg_str.parts.begin(), arg_str.parts.end());
+            }
+            flush_literal();
+            return mk_val<value_string>(result);
+        }},
         {"int", [](const func_args & args) -> value {
             value val_input   = args.get_pos(0);
             value val_default = args.get_kwarg_or_pos("default", 1);
             value val_base    = args.get_kwarg_or_pos("base",    2);
             const int base = val_base->is_undefined() ? 10 : val_base->as_int();
+            if (base != 0 && (base < 2 || base > 36)) {
+                // an out-of-range base makes std::stoi fail fast on the MSVC CRT instead of throwing
+                throw raised_exception("int() base must be 0 or between 2 and 36");
+            }
             if (is_val<value_string>(val_input) == false) {
                 throw raised_exception("int() first argument must be a string");
             }

conversion/__init__.py

@@ -106,6 +106,7 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "HunYuanDenseV1ForCausalLM": "hunyuan",
     "HunYuanMoEV1ForCausalLM": "hunyuan",
     "HunYuanVLForConditionalGeneration": "hunyuan",
+    "HYV3ForCausalLM": "hunyuan",
     "IQuestCoderForCausalLM": "llama",
     "InternLM2ForCausalLM": "internlm",
     "InternLM3ForCausalLM": "internlm",

conversion/hunyuan.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import json
+import re
 
 from pathlib import Path
 from typing import Callable, Iterable, TYPE_CHECKING
@@ -355,3 +356,105 @@ class HunyuanVLTextModel(HunYuanModel):
         self.gguf_writer.add_context_length(ctx_len)
 
         self.gguf_writer.add_rope_dimension_sections(list(self.rope_parameters["xdrope_section"]))
+
+
+@ModelBase.register("HYV3ForCausalLM")
+class HYV3Model(TextModel):
+    model_arch = gguf.MODEL_ARCH.HY_V3
+
+    # Trunk layer count, stashed before indexing so the classmethod
+    # filter_tensors can identify the appended MTP block(s) (mirrors
+    # Step35Model).
+    _n_main_layers: int | None = None
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        # NextN/MTP layers are appended past num_hidden_layers; extend the
+        # tensor map so the MTP block's tensors resolve to blk.<n>.* names.
+        n_nextn = int(self.hparams.get("num_nextn_predict_layers", 0))
+        if n_nextn > 0 and not self.no_mtp:
+            self.block_count += n_nextn
+            self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
+
+    def index_tensors(self, remote_hf_model_id: str | None = None):
+        type(self)._n_main_layers = self.hparams["num_hidden_layers"]
+        return super().index_tensors(remote_hf_model_id=remote_hf_model_id)
+
+    def set_vocab(self):
+        self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        self.gguf_writer.add_expert_feed_forward_length(self.hparams["moe_intermediate_size"])
+        self.gguf_writer.add_expert_shared_feed_forward_length(
+            self.hparams["moe_intermediate_size"] * self.hparams.get("num_shared_experts", 1)
+        )
+        self.gguf_writer.add_expert_weights_norm(self.hparams.get("route_norm", True))
+        self.gguf_writer.add_expert_weights_scale(float(self.hparams.get("router_scaling_factor", 1.0)))
+        # sigmoid router with expert selection bias
+        self.gguf_writer.add_expert_gating_func(gguf.ExpertGatingFuncType.SIGMOID)
+
+        n_nextn = int(self.hparams.get("num_nextn_predict_layers", 0))
+        if n_nextn > 0 and not self.no_mtp:
+            self.gguf_writer.add_nextn_predict_layers(n_nextn)
+
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        if (titem := super().filter_tensors(item)) is None:
+            return None
+        name, gen = titem
+
+        # HY V3 appends the MTP block(s) past num_hidden_layers.
+        assert cls._n_main_layers is not None
+        is_mtp = (m := re.match(r"model\.layers\.(\d+)\.", name)) is not None and int(m.group(1)) >= cls._n_main_layers
+
+        # --no-mtp: drop the appended MTP block(s) entirely.
+        if is_mtp and cls.no_mtp:
+            return None
+        # --mtp: keep ONLY MTP-block tensors plus the shared embeddings/norm/
+        # lm_head (so the resulting GGUF carries just the draft head).
+        if cls.mtp_only and not is_mtp and name not in (
+            "model.embed_tokens.weight", "model.norm.weight", "lm_head.weight",
+        ):
+            return None
+
+        # The MTP block's trailing final_layernorm (applied after the decoder
+        # block, before the shared LM head) maps to nextn.shared_head_norm.
+        if is_mtp:
+            name = name.replace(".final_layernorm.", ".shared_head.norm.")
+
+        return name, gen
+
+    _experts: list[dict[str, Tensor]] | None = None
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        # merge the per-expert tensors into stacked 3d tensors
+        if name.startswith("model.layers.") and ".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:
+                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]
+
+                    merged = torch.stack(datas, dim=0)
+                    yield from super().modify_tensors(merged, f"model.layers.{bid}.mlp.experts.{w_name}.weight", bid)
+            return
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
+    def prepare_tensors(self):
+        super().prepare_tensors()
+        if self._experts is not None:
+            experts = [k for d in self._experts for k in d.keys()]
+            if experts:
+                raise ValueError(f"Unprocessed experts: {experts}")

ggml/include/gguf.h

@@ -125,12 +125,13 @@ extern "C" {
     // get ith C string from array with given key_id
     GGML_API const char * gguf_get_arr_str (const struct gguf_context * ctx, int64_t key_id, size_t i);
 
-    GGML_API int64_t        gguf_get_n_tensors    (const struct gguf_context * ctx);
-    GGML_API int64_t        gguf_find_tensor      (const struct gguf_context * ctx, const char * name); // returns -1 if the tensor is not found
-    GGML_API size_t         gguf_get_tensor_offset(const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API const char *   gguf_get_tensor_name  (const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API enum ggml_type gguf_get_tensor_type  (const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API size_t         gguf_get_tensor_size  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API int64_t         gguf_get_n_tensors    (const struct gguf_context * ctx);
+    GGML_API int64_t         gguf_find_tensor      (const struct gguf_context * ctx, const char * name); // returns -1 if the tensor is not found
+    GGML_API size_t          gguf_get_tensor_offset(const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API const char *    gguf_get_tensor_name  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API const int64_t * gguf_get_tensor_ne    (const struct gguf_context * ctx, int64_t tensor_id); // returns ne, an array of GGML_MAX_DIMS elements; ne[dim] is 1 for dim >= n_dims
+    GGML_API enum ggml_type  gguf_get_tensor_type  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API size_t          gguf_get_tensor_size  (const struct gguf_context * ctx, int64_t tensor_id);
 
     // removes key if it exists, returns id that the key had prior to removal (-1 if it didn't exist)
     GGML_API int64_t gguf_remove_key(struct gguf_context * ctx, const char * key);

ggml/src/ggml-cuda/mmq-config-ampere.cuh

@@ -0,0 +1,366 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_ampere(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+
+    return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 1, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
+}

ggml/src/ggml-cuda/mmq-config-blackwell.cuh

@@ -0,0 +1,37 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_blackwell(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_MXFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, true);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+    CASE(GGML_TYPE_NVFP4, 256, 1, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_FP4, MMQ_ITER_K_FP4, true, false);
+
+    return ggml_cuda_mmq_get_config_ampere(type, J, fallback);
+}

ggml/src/ggml-cuda/mmq-config-cdna.cuh

@@ -0,0 +1,177 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_cdna(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q1_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_1, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_1, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q8_0, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q2_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q3_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q4_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q5_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_Q6_K, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ1_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XXS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_XS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ2_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_XXS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ3_S, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_XS, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_IQ4_NL, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, true, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_MXFP4, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, true, false);
+
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, true);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+    CASE(GGML_TYPE_NVFP4, 512, 1, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, true, false);
+
+    return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 512, 1, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
+}

ggml/src/ggml-cuda/mmq-config-pascal.cuh

@@ -0,0 +1,261 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_pascal(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 64,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+
+    return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
+}

ggml/src/ggml-cuda/mmq-config-rdna2.cuh

@@ -0,0 +1,261 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_rdna2(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,   8, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  24, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  40, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+
+    return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
+}

ggml/src/ggml-cuda/mmq-config-rdna4.cuh

@@ -0,0 +1,282 @@
+static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_rdna4(ggml_type type, int J, bool fallback) {
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q2_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
+
+// ---------------------------------------------------------------------------------------------
+
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
+
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  80, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128,  96, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+    CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+
+    return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
+}

ggml/src/ggml-cuda/mmq.cu

@@ -3,6 +3,8 @@
 #include "quantize.cuh"
 #include "mmid.cuh"
 
+#include <cstdint>
+
 static void ggml_cuda_mul_mat_q_switch_type(ggml_backend_cuda_context & ctx, const mmq_args & args, cudaStream_t stream) {
     switch (args.type_x) {
         case GGML_TYPE_Q1_0:
@@ -118,15 +120,14 @@ void ggml_cuda_mul_mat_q(
     const int64_t s03 = src0->nb[3] / ts_src0;
     const int64_t s3  =  dst->nb[3] / ts_dst;
 
-    const bool use_stream_k = (GGML_CUDA_CC_IS_NVIDIA(cc) && ggml_cuda_highest_compiled_arch(cc) >= GGML_CUDA_CC_VOLTA)
-                            || GGML_CUDA_CC_IS_CDNA(cc);
+    const bool fallback = ne01 % 128 != 0;
 
     // TODO: tighter pool buffer size vs q8 path
     const bool use_native_fp4 = blackwell_mma_available(cc) && (src0->type == GGML_TYPE_MXFP4 || src0->type == GGML_TYPE_NVFP4);
 
     if (!ids) {
         const size_t nbytes_src1_q8_1 = ne13*ne12 * ne11*ne10_padded * sizeof(block_q8_1)/QK8_1 +
-            get_mmq_x_max_host(cc)*sizeof(block_q8_1_mmq);
+            ggml_cuda_mmq_get_J_max(src0->type, fallback, cc, ne11) * sizeof(block_q8_1_mmq);
         ggml_cuda_pool_alloc<char> src1_q8_1(ctx.pool(), nbytes_src1_q8_1);
 
         {
@@ -156,7 +157,7 @@ void ggml_cuda_mul_mat_q(
             ne00, ne01, ne1, s01, ne11, s1,
             ne02, ne12, s02, s12, s2,
             ne03, ne13, s03, s13, s3,
-            use_stream_k, ne1};
+            ne1};
         ggml_cuda_mul_mat_q_switch_type(ctx, args, stream);
         return;
     }
@@ -184,7 +185,7 @@ void ggml_cuda_mul_mat_q(
     }
 
     const size_t nbytes_src1_q8_1 = ne12*n_expert_used*ne10_padded * sizeof(block_q8_1)/QK8_1 +
-        get_mmq_x_max_host(cc)*sizeof(block_q8_1_mmq);
+        ggml_cuda_mmq_get_J_max(src0->type, fallback, cc, ne11) * sizeof(block_q8_1_mmq);
     ggml_cuda_pool_alloc<char> src1_q8_1(ctx.pool(), nbytes_src1_q8_1);
 
     const int64_t ne11_flat = ne12*n_expert_used;
@@ -217,53 +218,11 @@ void ggml_cuda_mul_mat_q(
         ne00, ne01, ne_get_rows, s01, ne_get_rows, s1,
         ne02, ne02, s02, s12, s2,
         ne03, ne13, s03, s13, s3,
-        use_stream_k, ne12};
+        ne12};
 
     ggml_cuda_mul_mat_q_switch_type(ctx, args, stream);
 }
 
-void ggml_cuda_op_mul_mat_q(
-    ggml_backend_cuda_context & ctx,
-    const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
-    const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
-    const int64_t src1_padded_row_size, cudaStream_t stream) {
-
-    const int64_t ne00 = src0->ne[0];
-
-    const int64_t ne10 = src1->ne[0];
-    const int64_t ne11 = src1->ne[1];
-    GGML_ASSERT(ne10 % QK8_1 == 0);
-
-    const int64_t ne0 = dst->ne[0];
-
-    const int64_t row_diff = row_high - row_low;
-    const int64_t stride01 = ne00 / ggml_blck_size(src0->type);
-
-    const int id = ggml_cuda_get_device();
-    const int cc = ggml_cuda_info().devices[id].cc;
-
-    // the main device has a larger memory buffer to hold the results from all GPUs
-    // nrows_dst == nrows of the matrix that the kernel writes into
-    const int64_t nrows_dst = id == ctx.device ? ne0 : row_diff;
-
-    // The stream-k decomposition is only faster for recent NVIDIA GPUs.
-    // Also its fixup needs to allocate a temporary buffer in the memory pool.
-    // There are multiple parallel CUDA streams for src1_ncols != ne11 which would introduce a race condition for this buffer.
-    const bool use_stream_k = ((GGML_CUDA_CC_IS_NVIDIA(cc) && ggml_cuda_highest_compiled_arch(cc) >= GGML_CUDA_CC_VOLTA)
-                            || GGML_CUDA_CC_IS_CDNA(cc))
-                            && src1_ncols == ne11;
-    const mmq_args args = {
-        src0_dd_i, src0->type, (const int *) src1_ddq_i, nullptr, nullptr, dst_dd_i,
-        ne00, row_diff, src1_ncols, stride01, ne11, nrows_dst,
-        1, 1, 0, 0, 0,
-        1, 1, 0, 0, 0,
-        use_stream_k, src1_ncols};
-
-    ggml_cuda_mul_mat_q_switch_type(ctx, args, stream);
-
-    GGML_UNUSED_VARS(src1, dst, src1_ddf_i, src1_padded_row_size);
-}
-
 bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11, int64_t n_experts) {
 #ifdef GGML_CUDA_FORCE_CUBLAS
     return false;

ggml/src/ggml-vulkan/CMakeLists.txt

@@ -97,6 +97,18 @@ if (Vulkan_FOUND)
         "GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT"
     )
 
+    test_shader_extension_support(
+        "GL_EXT_float_e2m1"
+        "${CMAKE_CURRENT_SOURCE_DIR}/vulkan-shaders/feature-tests/float_e2m1.comp"
+        "GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT"
+    )
+
+    test_shader_extension_support(
+        "GL_EXT_float_e4m3"
+        "${CMAKE_CURRENT_SOURCE_DIR}/vulkan-shaders/feature-tests/float_e4m3.comp"
+        "GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT"
+    )
+
     target_link_libraries(ggml-vulkan PRIVATE Vulkan::Vulkan)
     target_include_directories(ggml-vulkan PRIVATE ${CMAKE_CURRENT_BINARY_DIR})
 

ggml/src/ggml-vulkan/ggml-vulkan.cpp

@@ -128,6 +128,34 @@ typedef struct VkPhysicalDeviceShaderMixedFloatDotProductFeaturesVALVE {
 } VkPhysicalDeviceShaderMixedFloatDotProductFeaturesVALVE;
 #endif
 
+#if !defined(VK_EXT_shader_ocp_microscaling_types)
+#define VK_EXT_shader_ocp_microscaling_types 1
+#define VK_EXT_SHADER_OCP_MICROSCALING_TYPES_SPEC_VERSION 1
+#define VK_EXT_SHADER_OCP_MICROSCALING_TYPES_EXTENSION_NAME "VK_EXT_shader_ocp_microscaling_types"
+#define VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_OCP_MICROSCALING_TYPES_FEATURES_EXT ((VkStructureType)1000672000)
+typedef struct VkPhysicalDeviceShaderOCPMicroscalingTypesFeaturesEXT {
+    VkStructureType    sType;
+    void*              pNext;
+    VkBool32           shaderFloat4;
+    VkBool32           shaderFloat6;
+    VkBool32           shaderFloat8UnsignedE8M0;
+    VkBool32           shaderMXInt8;
+} VkPhysicalDeviceShaderOCPMicroscalingTypesFeaturesEXT;
+#endif
+
+#if !defined(VK_EXT_shader_float8)
+#define VK_EXT_shader_float8 1
+#define VK_EXT_SHADER_FLOAT8_SPEC_VERSION 1
+#define VK_EXT_SHADER_FLOAT8_EXTENSION_NAME "VK_EXT_shader_float8"
+#define VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_FLOAT8_FEATURES_EXT ((VkStructureType)1000567000)
+typedef struct VkPhysicalDeviceShaderFloat8FeaturesEXT {
+    VkStructureType    sType;
+    void*              pNext;
+    VkBool32           shaderFloat8;
+    VkBool32           shaderFloat8CooperativeMatrix;
+} VkPhysicalDeviceShaderFloat8FeaturesEXT;
+#endif
+
 #define ROUNDUP_POW2(M, N) (((M) + (N) - 1) & ~((N) - 1))
 #define CEIL_DIV(M, N) (((M) / (N)) + (((M) % (N)) != 0))
 static bool is_pow2(uint32_t x) { return x > 1 && (x & (x-1)) == 0; }
@@ -745,6 +773,7 @@ struct vk_device_struct {
     bool coopmat2_decode_vector;
 
     bool dot2_f16 {};
+    bool ocp_fp4 {};
 
     bool pipeline_executable_properties_support {};
 
@@ -4310,8 +4339,16 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
         CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ3_S],   matmul_iq3_s_f16,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
         CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ4_XS],  matmul_iq4_xs_f16,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
         CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ4_NL],  matmul_iq4_nl_f16,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_MXFP4],   matmul_mxfp4_f16,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_NVFP4],   matmul_nvfp4_f16,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if (device->ocp_fp4) {
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_MXFP4],   matmul_mxfp4_f16_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_NVFP4],   matmul_nvfp4_f16_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
+        } else
+#endif
+        {
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_MXFP4],   matmul_mxfp4_f16,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_NVFP4],   matmul_nvfp4_f16,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
+        }
 
         GGML_ASSERT(device->subgroup_ballot);
 
@@ -4341,8 +4378,16 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
         CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S],   matmul_id_subgroup_iq3_s_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
         CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_subgroup_iq4_xs_f16,  mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
         CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_subgroup_iq4_nl_f16,  mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if (device->ocp_fp4) {
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f16_ocp,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f16_ocp,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        } else
+#endif
+        {
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+            CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        }
 #undef CREATE_MM
 #undef CREATE_MM2
     } else
@@ -4383,54 +4428,37 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
         }
 #endif
 
-        if (device->coopmat_acc_f16_support) {
-            CREATE_MM2(GGML_TYPE_Q1_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q1_0], matmul_q1_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0], matmul_q4_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1], matmul_q4_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0], matmul_q5_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1], matmul_q5_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0], matmul_q8_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q1_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q1_0], matmul_q1_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0], matmul_q4_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1], matmul_q4_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0], matmul_q5_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1], matmul_q5_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0], matmul_q8_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
 
-            CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K], matmul_q2_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K], matmul_q3_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K], matmul_q4_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K], matmul_q5_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K], matmul_q6_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_S],   matmul_iq1_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_M],   matmul_iq1_m_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS], matmul_iq2_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS],  matmul_iq2_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S],   matmul_iq2_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS], matmul_iq3_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S],   matmul_iq3_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_XS],  matmul_iq4_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL],  matmul_iq4_nl_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K], matmul_q2_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K], matmul_q3_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K], matmul_q4_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K], matmul_q5_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K], matmul_q6_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_S],   matmul_iq1_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_M],   matmul_iq1_m_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS], matmul_iq2_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS],  matmul_iq2_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S],   matmul_iq2_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS], matmul_iq3_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S],   matmul_iq3_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_XS],  matmul_iq4_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL],  matmul_iq4_nl_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if (device->ocp_fp4) {
+            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_MXFP4],   matmul_mxfp4_f32_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+            CREATE_MM2(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_NVFP4],   matmul_nvfp4_f32_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
+        } else
+#endif
+        {
             CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_MXFP4],   matmul_mxfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
             CREATE_MM2(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_NVFP4],   matmul_nvfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-        } else {
-            CREATE_MM(GGML_TYPE_Q1_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q1_0].f32acc, matmul_q1_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0].f32acc, matmul_q4_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1].f32acc, matmul_q4_1_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0].f32acc, matmul_q5_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1].f32acc, matmul_q5_1_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0].f32acc, matmul_q8_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-
-            CREATE_MM(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K].f32acc, matmul_q2_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K].f32acc, matmul_q3_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f32acc, matmul_q4_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f32acc, matmul_q5_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f32acc, matmul_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_S].f32acc,   matmul_iq1_s_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ1_M].f32acc,   matmul_iq1_m_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS].f32acc, matmul_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS].f32acc,  matmul_iq2_xs_f32,  , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S].f32acc,   matmul_iq2_s_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS].f32acc, matmul_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S].f32acc,   matmul_iq3_s_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_XS].f32acc,  matmul_iq4_xs_f32,  , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f32acc,  matmul_iq4_nl_f32,  , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_MXFP4].f32acc,   matmul_mxfp4_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
-            CREATE_MM(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat[GGML_TYPE_NVFP4].f32acc,   matmul_nvfp4_f32,   , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
         }
 
         GGML_ASSERT(device->subgroup_ballot);
@@ -4464,8 +4492,16 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
         CREATE_MM2(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S],   matmul_id_subgroup_iq3_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
         CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_subgroup_iq4_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
         CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_subgroup_iq4_nl_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
-        CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
-        CREATE_MM2(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if (device->ocp_fp4) {
+            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+            CREATE_MM2(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f32_ocp,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        } else
+#endif
+        {
+            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+            CREATE_MM2(GGML_TYPE_NVFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_NVFP4],   matmul_id_subgroup_nvfp4_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        }
 #undef CREATE_MM2
 #undef CREATE_MM
     } else
@@ -4844,6 +4880,14 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
     static constexpr uint32_t mul_mat_vec_num_bindings = 5;
     static constexpr uint32_t mul_mat_vec_id_num_bindings = 6;
 
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+#define OCP_DMMV_LEN(NAME, REDUC)  (device->ocp_fp4 ? NAME ## _ocp_len[REDUC]  : NAME ## _len[REDUC])
+#define OCP_DMMV_DATA(NAME, REDUC) (device->ocp_fp4 ? NAME ## _ocp_data[REDUC] : NAME ## _data[REDUC])
+#else
+#define OCP_DMMV_LEN(NAME, REDUC)  NAME ## _len[REDUC]
+#define OCP_DMMV_DATA(NAME, REDUC) NAME ## _data[REDUC]
+#endif
+
     for (uint32_t w = 0; w < DMMV_WG_SIZE_COUNT; ++w) {
         const uint32_t wg_size_subgroup   = (w == DMMV_WG_SIZE_SUBGROUP) ? subgroup_size : (subgroup_size * 4);
         const uint32_t wg_size_subgroup16 = (w == DMMV_WG_SIZE_SUBGROUP) ? subgroup_size16 : (subgroup_size16 * 4);
@@ -4880,8 +4924,8 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_IQ3_S][i],   "mul_mat_vec_iq3_s_f32_f32",   arr_dmmv_iq3_s_f32_f32_len[reduc16],   arr_dmmv_iq3_s_f32_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_IQ4_XS][i],  "mul_mat_vec_iq4_xs_f32_f32",  arr_dmmv_iq4_xs_f32_f32_len[reduc16],  arr_dmmv_iq4_xs_f32_f32_data[reduc16],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_IQ4_NL][i],  "mul_mat_vec_iq4_nl_f32_f32",  arr_dmmv_iq4_nl_f32_f32_len[reduc16],  arr_dmmv_iq4_nl_f32_f32_data[reduc16],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
-            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_MXFP4][i],   "mul_mat_vec_mxfp4_f32_f32",   arr_dmmv_mxfp4_f32_f32_len[reduc16],   arr_dmmv_mxfp4_f32_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
-            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_NVFP4][i],   "mul_mat_vec_nvfp4_f32_f32",   arr_dmmv_nvfp4_f32_f32_len[reduc16],   arr_dmmv_nvfp4_f32_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
+            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_MXFP4][i],   "mul_mat_vec_mxfp4_f32_f32",   OCP_DMMV_LEN(arr_dmmv_mxfp4_f32_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_mxfp4_f32_f32, reduc16), "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
+            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_NVFP4][i],   "mul_mat_vec_nvfp4_f32_f32",   OCP_DMMV_LEN(arr_dmmv_nvfp4_f32_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_nvfp4_f32_f32, reduc16), "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
 
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f16_f32",  arr_dmmv_f32_f16_f32_len[reduc],  arr_dmmv_f32_f16_f32_data[reduc],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, {wg_size_subgroup, 1, i+1}, 1, false, use_subgroups, force_subgroup_size);
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_F16 ][i], "mul_mat_vec_f16_f16_f32",  arr_dmmv_f16_f16_f32_len[reduc],  arr_dmmv_f16_f16_f32_data[reduc],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size);
@@ -4906,8 +4950,8 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_IQ3_S][i],   "mul_mat_vec_iq3_s_f16_f32",   arr_dmmv_iq3_s_f16_f32_len[reduc16],   arr_dmmv_iq3_s_f16_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_IQ4_XS][i],  "mul_mat_vec_iq4_xs_f16_f32",  arr_dmmv_iq4_xs_f16_f32_len[reduc16],  arr_dmmv_iq4_xs_f16_f32_data[reduc16],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
             ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_IQ4_NL][i],  "mul_mat_vec_iq4_nl_f16_f32",  arr_dmmv_iq4_nl_f16_f32_len[reduc16],  arr_dmmv_iq4_nl_f16_f32_data[reduc16],  "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
-            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_MXFP4][i],   "mul_mat_vec_mxfp4_f16_f32",   arr_dmmv_mxfp4_f16_f32_len[reduc16],   arr_dmmv_mxfp4_f16_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
-            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_NVFP4][i],   "mul_mat_vec_nvfp4_f16_f32",   arr_dmmv_nvfp4_f16_f32_len[reduc16],   arr_dmmv_nvfp4_f16_f32_data[reduc16],   "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
+            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_MXFP4][i],   "mul_mat_vec_mxfp4_f16_f32",   OCP_DMMV_LEN(arr_dmmv_mxfp4_f16_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_mxfp4_f16_f32, reduc16), "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
+            ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_NVFP4][i],   "mul_mat_vec_nvfp4_f16_f32",   OCP_DMMV_LEN(arr_dmmv_nvfp4_f16_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_nvfp4_f16_f32, reduc16), "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16);
 
 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
             if (device->integer_dot_product) {
@@ -4958,8 +5002,8 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
         ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_IQ3_S],   "mul_mat_vec_id_iq3_s_f32",   arr_dmmv_id_iq3_s_f32_f32_len[reduc16],   arr_dmmv_id_iq3_s_f32_f32_data[reduc16],   "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
         ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_IQ4_XS],  "mul_mat_vec_id_iq4_xs_f32",  arr_dmmv_id_iq4_xs_f32_f32_len[reduc16],  arr_dmmv_id_iq4_xs_f32_f32_data[reduc16],  "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
         ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_IQ4_NL],  "mul_mat_vec_id_iq4_nl_f32",  arr_dmmv_id_iq4_nl_f32_f32_len[reduc16],  arr_dmmv_id_iq4_nl_f32_f32_data[reduc16],  "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
-        ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_MXFP4],   "mul_mat_vec_id_mxfp4_f32",   arr_dmmv_id_mxfp4_f32_f32_len[reduc16],   arr_dmmv_id_mxfp4_f32_f32_data[reduc16],   "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
-        ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_NVFP4],   "mul_mat_vec_id_nvfp4_f32",   arr_dmmv_id_nvfp4_f32_f32_len[reduc16],   arr_dmmv_id_nvfp4_f32_f32_data[reduc16],   "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
+        ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_MXFP4],   "mul_mat_vec_id_mxfp4_f32",   OCP_DMMV_LEN(arr_dmmv_id_mxfp4_f32_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_id_mxfp4_f32_f32, reduc16), "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
+        ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_NVFP4],   "mul_mat_vec_id_nvfp4_f32",   OCP_DMMV_LEN(arr_dmmv_id_nvfp4_f32_f32, reduc16), OCP_DMMV_DATA(arr_dmmv_id_nvfp4_f32_f32, reduc16), "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq}, 1, true, use_subgroups16, force_subgroup_size16);
 
 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
         if (device->integer_dot_product) {
@@ -4986,6 +5030,9 @@ static void ggml_vk_load_shaders(vk_device& device, vk_pipeline requested) {
 #endif // GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT
     }
 
+#undef OCP_DMMV_DATA
+#undef OCP_DMMV_LEN
+
 #if !defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
     GGML_UNUSED(rm_stdq_int);
     GGML_UNUSED(rm_kq_int);
@@ -5795,6 +5842,8 @@ static vk_device ggml_vk_get_device(size_t idx) {
         device->shader_64b_indexing = false;
         bool bfloat16_support = false;
         bool dot2_f16_support = false;
+        bool ocp_microscaling_extension = false;
+        bool shader_float8_extension = false;
 
         for (const auto& properties : ext_props) {
             if (strcmp("VK_KHR_maintenance4", properties.extensionName) == 0) {
@@ -5836,6 +5885,14 @@ static vk_device ggml_vk_get_device(size_t idx) {
             } else if (strcmp("VK_KHR_shader_bfloat16", properties.extensionName) == 0 &&
                        !getenv("GGML_VK_DISABLE_BFLOAT16")) {
                 bfloat16_support = true;
+#endif
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT)
+            } else if (strcmp(VK_EXT_SHADER_OCP_MICROSCALING_TYPES_EXTENSION_NAME, properties.extensionName) == 0) {
+                ocp_microscaling_extension = true;
+#endif
+#if defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+            } else if (strcmp(VK_EXT_SHADER_FLOAT8_EXTENSION_NAME, properties.extensionName) == 0) {
+                shader_float8_extension = true;
 #endif
             } else if (strcmp("VK_VALVE_shader_mixed_float_dot_product", properties.extensionName) == 0 &&
                        !getenv("GGML_VK_DISABLE_DOT2")) {
@@ -6139,6 +6196,22 @@ static vk_device ggml_vk_get_device(size_t idx) {
         }
 #endif
 
+        VkPhysicalDeviceShaderOCPMicroscalingTypesFeaturesEXT ocp_microscaling_features {};
+        ocp_microscaling_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_OCP_MICROSCALING_TYPES_FEATURES_EXT;
+        if (ocp_microscaling_extension) {
+            last_struct->pNext = (VkBaseOutStructure *)&ocp_microscaling_features;
+            last_struct = (VkBaseOutStructure *)&ocp_microscaling_features;
+            device_extensions.push_back(VK_EXT_SHADER_OCP_MICROSCALING_TYPES_EXTENSION_NAME);
+        }
+
+        VkPhysicalDeviceShaderFloat8FeaturesEXT shader_float8_features {};
+        shader_float8_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_FLOAT8_FEATURES_EXT;
+        if (shader_float8_extension) {
+            last_struct->pNext = (VkBaseOutStructure *)&shader_float8_features;
+            last_struct = (VkBaseOutStructure *)&shader_float8_features;
+            device_extensions.push_back(VK_EXT_SHADER_FLOAT8_EXTENSION_NAME);
+        }
+
         VkPhysicalDeviceMaintenance4Features maint4_features {};
         maint4_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_MAINTENANCE_4_FEATURES;
         if (maintenance4_support) {
@@ -6198,6 +6271,9 @@ static vk_device ggml_vk_get_device(size_t idx) {
 #endif
 
         device->dot2_f16 = dot2_f16_support && dot2_features.shaderMixedFloatDotProductFloat16AccFloat32;
+        device->ocp_fp4 = ocp_microscaling_extension && ocp_microscaling_features.shaderFloat4 &&
+                          shader_float8_extension && shader_float8_features.shaderFloat8 &&
+                          !getenv("GGML_VK_DISABLE_OCP_FP4");
 
         device->pipeline_robustness = pl_robustness_features.pipelineRobustness;
 
@@ -6634,6 +6710,8 @@ static void ggml_vk_print_gpu_info(size_t idx) {
     bool integer_dot_product = false;
     bool bfloat16_support = false;
     bool dot2_f16_support = false;
+    bool ocp_microscaling_extension = false;
+    bool shader_float8_extension = false;
 
     for (auto properties : ext_props) {
         if (strcmp("VK_KHR_16bit_storage", properties.extensionName) == 0) {
@@ -6662,6 +6740,14 @@ static void ggml_vk_print_gpu_info(size_t idx) {
         } else if (strcmp("VK_KHR_shader_bfloat16", properties.extensionName) == 0 &&
                     !getenv("GGML_VK_DISABLE_BFLOAT16")) {
             bfloat16_support = true;
+#endif
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT)
+        } else if (strcmp(VK_EXT_SHADER_OCP_MICROSCALING_TYPES_EXTENSION_NAME, properties.extensionName) == 0) {
+            ocp_microscaling_extension = true;
+#endif
+#if defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        } else if (strcmp(VK_EXT_SHADER_FLOAT8_EXTENSION_NAME, properties.extensionName) == 0) {
+            shader_float8_extension = true;
 #endif
         } else if (strcmp("VK_VALVE_shader_mixed_float_dot_product", properties.extensionName) == 0 &&
                     !getenv("GGML_VK_DISABLE_DOT2")) {
@@ -6763,6 +6849,21 @@ static void ggml_vk_print_gpu_info(size_t idx) {
         last_struct = (VkBaseOutStructure *)&dot2_features;
     }
 
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+    VkPhysicalDeviceShaderOCPMicroscalingTypesFeaturesEXT ocp_microscaling_features {};
+    ocp_microscaling_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_OCP_MICROSCALING_TYPES_FEATURES_EXT;
+    VkPhysicalDeviceShaderFloat8FeaturesEXT shader_float8_features {};
+    shader_float8_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_FLOAT8_FEATURES_EXT;
+    if (ocp_microscaling_extension) {
+        last_struct->pNext = (VkBaseOutStructure *)&ocp_microscaling_features;
+        last_struct = (VkBaseOutStructure *)&ocp_microscaling_features;
+    }
+    if (shader_float8_extension) {
+        last_struct->pNext = (VkBaseOutStructure *)&shader_float8_features;
+        last_struct = (VkBaseOutStructure *)&shader_float8_features;
+    }
+#endif
+
     vkGetPhysicalDeviceFeatures2(physical_device, &device_features2);
 
     fp16 = fp16 && vk12_features.shaderFloat16;
@@ -6811,10 +6912,19 @@ static void ggml_vk_print_gpu_info(size_t idx) {
 
     bool dot2_f16 = dot2_f16_support && dot2_features.shaderMixedFloatDotProductFloat16AccFloat32;
     const char *fp16_str = fp16 ? (dot2_f16 ? "dot2" : "1") : "0";
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+    const bool fp4 = ocp_microscaling_extension && ocp_microscaling_features.shaderFloat4 &&
+                     shader_float8_extension && shader_float8_features.shaderFloat8 &&
+                     !getenv("GGML_VK_DISABLE_OCP_FP4");
+#else
+    GGML_UNUSED(ocp_microscaling_extension);
+    GGML_UNUSED(shader_float8_extension);
+    const bool fp4 = false;
+#endif
 
     std::string device_name = props2.properties.deviceName.data();
-    GGML_LOG_DEBUG("ggml_vulkan: %zu = %s (%s) | uma: %d | fp16: %s | bf16: %d | warp size: %zu | shared memory: %d | int dot: %d | matrix cores: %s\n",
-              idx, device_name.c_str(), driver_props.driverName.data(), uma, fp16_str, bf16, subgroup_size,
+    GGML_LOG_DEBUG("ggml_vulkan: %zu = %s (%s) | uma: %d | fp16: %s | bf16: %d | fp4: %d | warp size: %zu | shared memory: %d | int dot: %d | matrix cores: %s\n",
+              idx, device_name.c_str(), driver_props.driverName.data(), uma, fp16_str, bf16, fp4, subgroup_size,
               props2.properties.limits.maxComputeSharedMemorySize, integer_dot_product, matrix_cores.c_str());
 
     if (props2.properties.deviceType == vk::PhysicalDeviceType::eCpu) {

ggml/src/ggml-vulkan/vulkan-shaders/CMakeLists.txt

@@ -23,6 +23,14 @@ if (GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
     add_compile_definitions(GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
     message(STATUS "Enabling bfloat16 glslc support")
 endif()
+if (GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT)
+    add_compile_definitions(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT)
+    message(STATUS "Enabling E2M1 glslc support")
+endif()
+if (GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+    add_compile_definitions(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+    message(STATUS "Enabling E4M3 glslc support")
+endif()
 if (GGML_VULKAN_SHADER_DEBUG_INFO)
     add_compile_definitions(GGML_VULKAN_SHADER_DEBUG_INFO)
     message(STATUS "Enabling shader debug info")

ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl

@@ -480,12 +480,22 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
 #if defined(DATA_A_MXFP4)
 vec2 dequantize(uint ib, uint iqs, uint a_offset) {
     const uint vui = uint(data_a[a_offset + ib].qs[iqs]);
+#ifdef USE_OCP_FP4
+    return vec2(unpackFloat2xfe2m1EXT(uint8_t(vui)));
+#else
     return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]) * 0.5;
+#endif
 }
 vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
+#ifdef USE_OCP_FP4
+    const uint16_t vui = uint16_t(uint(data_a[a_offset + ib].qs[iqs]) |
+                                  uint(data_a[a_offset + ib].qs[iqs + 1]) << 8);
+    return vec4(unpackFloat4xfe2m1EXT(vui));
+#else
     vec2 v0 = dequantize(ib, iqs, a_offset);
     vec2 v1 = dequantize(ib, iqs + 1, a_offset);
     return vec4(v0.x, v0.y, v1.x, v1.y);
+#endif
 }
 #endif
 
@@ -495,16 +505,30 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
     const float d = ue4m3_to_fp32(data_a[a_offset + ib].d[sub]);
     const uint j = iqs & 7;
     const uint shift = (iqs & 8) >> 1; // 0 or 4
+#ifdef USE_OCP_FP4
+    const uint vui = uint(data_a_packed16[a_offset + ib].qs[(sub * 8u + j) / 2u]);
+    return vec2(bitcastExtractfe2m1EXT(unpack8(vui).xy, shift)) * d;
+#else
     const uint vui0 = uint(data_a[a_offset + ib].qs[sub * 8u + j]);
     const uint vui1 = uint(data_a[a_offset + ib].qs[sub * 8u + j + 1]);
     const uint qs0 = (vui0 >> shift) & 0xF;
     const uint qs1 = (vui1 >> shift) & 0xF;
     return vec2(float(kvalues_mxfp4[qs0]), float(kvalues_mxfp4[qs1])) * d * 0.5;
+#endif
 }
 vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
+#ifdef USE_OCP_FP4
+    const uint sub = iqs >> 4;
+    const float d = ue4m3_to_fp32(data_a[a_offset + ib].d[sub]);
+    const uint j = iqs & 7;
+    const uint shift = (iqs & 8) >> 1; // 0 or 4
+    const uint vui = data_a_packed32[a_offset + ib].qs[(sub * 8u + j) / 4u];
+    return vec4(bitcastExtractfe2m1EXT(unpack8(vui), shift)) * d;
+#else
     const vec2 v0 = dequantize(ib, iqs, a_offset);
     const vec2 v1 = dequantize(ib, iqs + 2u, a_offset);
     return vec4(v0.x, v0.y, v1.x, v1.y);
+#endif
 }
 #endif
 

ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl

@@ -1232,11 +1232,15 @@ float16_t dequantFuncMXFP4(const in decodeBufMXFP4 bl, const in uint blockCoords
     const uint idx = coordInBlock[1];
     const uint iqs = idx & 0xF;
     const uint shift = (idx & 0x10) >> 2;
+#ifdef USE_OCP_FP4
+    return float16_t(bitcastExtractfe2m1EXT(bl.block.qs[iqs], shift)) * float16_t(d);
+#else
     uint32_t qs = bl.block.qs[iqs];
     qs >>= shift;
     qs &= 0xF;
     float16_t ret = float16_t(kvalues_mxfp4[qs] * d * 0.5);
     return ret;
+#endif
 }
 
 f16vec4 dequantFuncMXFP4_v(const in decodeBufMXFP4 bl, const in uint blockCoords[2], const in uint coordInBlock[2])
@@ -1245,6 +1249,16 @@ f16vec4 dequantFuncMXFP4_v(const in decodeBufMXFP4 bl, const in uint blockCoords
     const uint idx = coordInBlock[1];
     const uint iqs = idx & 0xF;
     const uint shift = (idx & 0x10) >> 2;
+#ifdef USE_OCP_FP4
+    const fe2m1vec4 qv = bitcastExtractfe2m1EXT(
+        u8vec4(
+            bl.block.qs[iqs],
+            bl.block.qs[iqs + 1u],
+            bl.block.qs[iqs + 2u],
+            bl.block.qs[iqs + 3u]),
+        shift);
+    return f16vec4(qv) * float16_t(d);
+#else
     uvec4 qv = uvec4(
         uint(bl.block.qs[iqs]),
         uint(bl.block.qs[iqs + 1u]),
@@ -1257,6 +1271,7 @@ f16vec4 dequantFuncMXFP4_v(const in decodeBufMXFP4 bl, const in uint blockCoords
         float(kvalues_mxfp4[qv.z]),
         float(kvalues_mxfp4[qv.w])) * d * 0.5f;
     return f16vec4(ret);
+#endif
 }
 #endif
 
@@ -1275,10 +1290,15 @@ float16_t dequantFuncNVFP4(const in decodeBufNVFP4 bl, const in uint blockCoords
     const uint sub = (idx & 0x30) >> 4;
     const uint iqs = ((idx & 0x30) >> 1) + (idx & 0x7);
     const uint shift = (idx & 0x8) >> 1;
+#ifdef USE_OCP_FP4
+    const float16_t d = float16_t(ue4m3_from_bits(bl.block.d[sub]));
+    return float16_t(bitcastExtractfe2m1EXT(bl.block.qs[iqs], shift)) * d;
+#else
     const float d = ue4m3_to_fp32(bl.block.d[sub]);
     uint qs = uint(bl.block.qs[iqs]);
     qs = (qs >> shift) & 0xF;
     return float16_t(kvalues_mxfp4[qs] * d * 0.5);
+#endif
 }
 
 f16vec4 dequantFuncNVFP4_v(const in decodeBufNVFP4 bl, const in uint blockCoords[2], const in uint coordInBlock[2])
@@ -1288,9 +1308,14 @@ f16vec4 dequantFuncNVFP4_v(const in decodeBufNVFP4 bl, const in uint blockCoords
     const uint sub   = idx >> 4;
     const uint qs_w  = ((idx & 0x30) >> 3) + ((idx & 0x4u) >> 2);  // iqs / 4, in [0,8)
     const uint shift = (idx & 0x8) >> 1;
-    const float d    = ue4m3_to_fp32(bl.block.d[sub]);
 
     const uint qsw  = uint32_t(bl32.block.qs[qs_w]);
+#ifdef USE_OCP_FP4
+    const float16_t d = float16_t(ue4m3_from_bits(bl.block.d[sub]));
+    const fe2m1vec4 qv = bitcastExtractfe2m1EXT(unpack8(qsw), shift);
+    return f16vec4(qv) * d;
+#else
+    const float d = ue4m3_to_fp32(bl.block.d[sub]);
     const u8vec4 qv = unpack8((qsw >> shift) & 0x0F0F0F0Fu);
     const vec4 ret = vec4(
         float(kvalues_mxfp4[qv.x]),
@@ -1298,6 +1323,7 @@ f16vec4 dequantFuncNVFP4_v(const in decodeBufNVFP4 bl, const in uint blockCoords
         float(kvalues_mxfp4[qv.z]),
         float(kvalues_mxfp4[qv.w])) * d * 0.5f;
     return f16vec4(ret);
+#endif
 }
 #endif
 

ggml/src/ggml-vulkan/vulkan-shaders/feature-tests/float_e2m1.comp

@@ -0,0 +1,7 @@
+#version 460
+
+#extension GL_EXT_float_e2m1 : require
+
+void main()
+{
+}

ggml/src/ggml-vulkan/vulkan-shaders/feature-tests/float_e4m3.comp

@@ -0,0 +1,7 @@
+#version 460
+
+#extension GL_EXT_float_e4m3 : require
+
+void main()
+{
+}

ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl

@@ -502,14 +502,21 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
             const uint ib = idx / 8;
             const uint iqs = (idx & 0x07) * 2;
 
-            const float d = e8m0_to_fp32(data_a[ib].e) * 0.5;
             const uint vui = uint(data_a[ib].qs[iqs]);
             const uint vui2 = uint(data_a[ib].qs[iqs+1]);
 
+#ifdef USE_OCP_FP4
+            const float d = e8m0_to_fp32(data_a[ib].e);
+            const u8vec2 packed = u8vec2(vui, vui2);
+            buf_a[buf_idx    ] = FLOAT_TYPEV2(bitcastExtractfe2m1EXT(packed, 0u)) * FLOAT_TYPE(d);
+            buf_a[buf_idx + 8] = FLOAT_TYPEV2(bitcastExtractfe2m1EXT(packed, 4u)) * FLOAT_TYPE(d);
+#else
+            const float d = e8m0_to_fp32(data_a[ib].e) * 0.5;
             buf_a[buf_idx    ] = FLOAT_TYPEV2(kvalues_mxfp4[vui  & 0xF] * d,
                                               kvalues_mxfp4[vui2 & 0xF] * d);
             buf_a[buf_idx + 8] = FLOAT_TYPEV2(kvalues_mxfp4[vui  >>  4] * d,
                                               kvalues_mxfp4[vui2 >>  4] * d);
+#endif
 #elif defined(DATA_A_NVFP4)
             const uint idx = pos_a + col * p.stride_a / LOAD_VEC_A + row;
             // lo and hi nibbles are 8 elements apart, which doesn't quite line up with
@@ -519,15 +526,22 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
             const uint ib = idx / 16u;
             const uint sub = (idx & 0xC) >> 2;
             const uint iqs = (idx & 0xF) * 2;
-            const float d = ue4m3_to_fp32(data_a[ib].d[sub]) * 0.5;
             const uint vui = uint(data_a[ib].qs[iqs]);
             const uint vui2 = uint(data_a[ib].qs[iqs+1]);
 
+#ifdef USE_OCP_FP4
+            const FLOAT_TYPE d = FLOAT_TYPE(ue4m3_from_bits(data_a[ib].d[sub]));
+            const u8vec2 packed = u8vec2(vui, vui2);
+            buf_a[buf_idx    ] = FLOAT_TYPEV2(bitcastExtractfe2m1EXT(packed, 0u)) * d;
+            buf_a[buf_idx + 4] = FLOAT_TYPEV2(bitcastExtractfe2m1EXT(packed, 4u)) * d;
+#else
+            const float d = ue4m3_to_fp32(data_a[ib].d[sub]) * 0.5;
             buf_a[buf_idx    ] = FLOAT_TYPEV2(kvalues_mxfp4[vui  & 0xF] * d,
                                               kvalues_mxfp4[vui2 & 0xF] * d);
             buf_a[buf_idx + 4] = FLOAT_TYPEV2(kvalues_mxfp4[vui  >>  4] * d,
                                               kvalues_mxfp4[vui2 >>  4] * d);
 #endif
+#endif
 }
 
 #if !defined(MUL_MAT_ID)

ggml/src/ggml-vulkan/vulkan-shaders/types.glsl

@@ -7,6 +7,11 @@
 #extension GL_EXT_shader_explicit_arithmetic_types_int8 : require
 #extension GL_EXT_shader_16bit_storage : require
 
+#ifdef USE_OCP_FP4
+#extension GL_EXT_float_e2m1 : require
+#extension GL_EXT_float_e4m3 : require
+#endif
+
 #if defined(DATA_A_F32)
 #define QUANT_K 1
 #define QUANT_R 1
@@ -1730,6 +1735,12 @@ struct block_nvfp4
     uint8_t qs[QUANT_K_NVFP4 / 2];
 };
 
+struct block_nvfp4_packed16
+{
+    uint16_t d[QUANT_K_NVFP4 / 16 / 2];
+    uint16_t qs[QUANT_K_NVFP4 / 2 / 2];
+};
+
 struct block_nvfp4_packed32
 {
     uint32_t d[QUANT_K_NVFP4 / 16 / 4];
@@ -1741,6 +1752,7 @@ struct block_nvfp4_packed32
 #define QUANT_R QUANT_R_NVFP4
 #define QUANT_AUXF 1
 #define A_TYPE block_nvfp4
+#define A_TYPE_PACKED16 block_nvfp4_packed16
 #define A_TYPE_PACKED32 block_nvfp4_packed32
 #endif
 
@@ -1764,14 +1776,16 @@ void init_iq_shmem(uvec3 wgsize)
 #endif
 
 #if defined(DATA_A_MXFP4) || defined(DATA_A_NVFP4)
+#if !defined(USE_OCP_FP4)
 const int8_t kvalues_mxfp4_const[16] = {
     int8_t(0), int8_t(1), int8_t(2), int8_t(3), int8_t(4), int8_t(6), int8_t(8), int8_t(12),
     int8_t(0), int8_t(-1), int8_t(-2), int8_t(-3), int8_t(-4), int8_t(-6), int8_t(-8), int8_t(-12),
 };
 
 shared int8_t kvalues_mxfp4[16];
+#endif
 
-#if defined(DATA_A_NVFP4)
+#if defined(DATA_A_NVFP4) && !defined(USE_OCP_FP4)
 // UE4M3 scale in NVFP4 blocks use only 7 bits; sign (bit 7) is always zero.
 shared float ue4m3_fp32_lut[128];
 
@@ -1789,6 +1803,7 @@ float ue4m3_to_fp32_build(uint u) {
 }
 #endif
 
+#if !defined(USE_OCP_FP4)
 #define NEEDS_INIT_IQ_SHMEM
 void init_iq_shmem(uvec3 wgsize)
 {
@@ -1804,6 +1819,7 @@ void init_iq_shmem(uvec3 wgsize)
     barrier();
 }
 #endif
+#endif
 
 // returns the bfloat value in the low 16b.
 // See ggml_compute_fp32_to_bf16
@@ -1838,8 +1854,21 @@ float e8m0_to_fp32(uint8_t x) {
 }
 
 #if defined(DATA_A_NVFP4)
+#if defined(USE_OCP_FP4)
+floate4m3_t ue4m3_from_bits(uint8_t x) {
+    if (x == uint8_t(0x7F)) {
+        return floate4m3_t(0.0);
+    }
+    return uintBitsToFloate4m3EXT(x);
+}
+#endif
+
 float ue4m3_to_fp32(uint8_t x) {
+#if defined(USE_OCP_FP4)
+    return float(ue4m3_from_bits(x));
+#else
     return ue4m3_fp32_lut[uint(x)];
+#endif
 }
 #endif
 

ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp

@@ -610,6 +610,15 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
             string_to_spv(shader_name + "_" + tname + "_f16" + dot2_sfx, source_name,  merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"B_TYPE_SCALAR", "float16_t"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}}), fp16, coopmat, coopmat2, f16acc);
         }
 
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if ((coopmat || coopmat2) && (tname == "mxfp4" || tname == "nvfp4")) {
+            if (!coopmat2) {
+                string_to_spv(shader_name + "_" + tname + "_f32_ocp" + dot2_sfx, source_name, merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"B_TYPE_SCALAR", "float"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}}), fp16, coopmat, coopmat2, f16acc);
+            }
+            string_to_spv(shader_name + "_" + tname + "_f16_ocp" + dot2_sfx, source_name, merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"B_TYPE_SCALAR", "float16_t"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}}), fp16, coopmat, coopmat2, f16acc);
+        }
+#endif
+
 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
         // Integer dot mmq performs better with f32 accumulators (different shader, skip for dot2)
         if (!f16acc && !coopmat && !coopmat2 && !dot2 && (is_legacy_quant(tname) || is_k_quant(tname) || tname == "mxfp4")) {
@@ -732,6 +741,20 @@ void process_shaders() {
         string_to_spv("mul_mat_vec_" + tname + "_f32_f32_subgroup_no_shmem", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
         string_to_spv("mul_mat_vec_" + tname + "_f16_f32_subgroup_no_shmem", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float16_t"}, {"B_TYPEV2", "f16vec2"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
 
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+        if (tname == "mxfp4" || tname == "nvfp4") {
+            string_to_spv("mul_mat_vec_" + tname + "_f32_f32_ocp", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}}));
+            string_to_spv("mul_mat_vec_" + tname + "_f16_f32_ocp", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float16_t"}, {"B_TYPEV2", "f16vec2"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}}));
+            string_to_spv("mul_mat_vec_" + tname + "_f32_f32_ocp_subgroup", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD", "1"}}));
+            string_to_spv("mul_mat_vec_" + tname + "_f16_f32_ocp_subgroup", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float16_t"}, {"B_TYPEV2", "f16vec2"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD", "1"}}));
+            string_to_spv("mul_mat_vec_" + tname + "_f32_f32_ocp_subgroup_no_shmem", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
+            string_to_spv("mul_mat_vec_" + tname + "_f16_f32_ocp_subgroup_no_shmem", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float16_t"}, {"B_TYPEV2", "f16vec2"}, {"B_TYPEV4", "f16vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
+            string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32_ocp", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}}));
+            string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32_ocp_subgroup", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD", "1"}}));
+            string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32_ocp_subgroup_no_shmem", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"USE_OCP_FP4", "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
+        }
+#endif
+
         string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}}));
         string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32_subgroup", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD", "1"}}));
         string_to_spv("mul_mat_vec_id_" + tname + "_f32_f32_subgroup_no_shmem", shader, merge_maps(base_dict, {{"MUL_MAT_ID", "1"}, {data_a_key, "1"}, {"B_TYPE", "float"}, {"B_TYPEV2", "vec2"}, {"B_TYPEV4", "vec4"}, {"D_TYPE", "float"}, {"USE_SUBGROUP_ADD_NO_SHMEM", "1"}}));
@@ -1233,6 +1256,27 @@ void write_output_files() {
     }
     }
 
+#if defined(GGML_VULKAN_FLOAT_E2M1_GLSLC_SUPPORT) && defined(GGML_VULKAN_FLOAT_E4M3_GLSLC_SUPPORT)
+    for (const std::string& btype : {"f16", "f32"}) {
+    for (const std::string& tname : {"mxfp4", "nvfp4"}) {
+        hdr << "extern const void * arr_dmmv_"   << tname << "_" << btype << "_f32_ocp_data[3];\n";
+        hdr << "extern const uint64_t arr_dmmv_" << tname << "_" << btype << "_f32_ocp_len[3];\n";
+        if (basename(input_filepath) == "mul_mat_vec.comp") {
+            src << "const void * arr_dmmv_"   << tname << "_" << btype << "_f32_ocp_data[3] = {mul_mat_vec_" << tname << "_" << btype << "_f32_ocp_data, mul_mat_vec_" << tname << "_" << btype << "_f32_ocp_subgroup_data, mul_mat_vec_" << tname << "_" << btype << "_f32_ocp_subgroup_no_shmem_data};\n";
+            src << "const uint64_t arr_dmmv_" << tname << "_" << btype << "_f32_ocp_len[3] =  {mul_mat_vec_" << tname << "_" << btype << "_f32_ocp_len,  mul_mat_vec_" << tname << "_" << btype << "_f32_ocp_subgroup_len, mul_mat_vec_"  << tname << "_" << btype << "_f32_ocp_subgroup_no_shmem_len};\n";
+        }
+    }
+    }
+    for (const std::string& tname : {"mxfp4", "nvfp4"}) {
+        hdr << "extern const void * arr_dmmv_id_"   << tname << "_f32_f32_ocp_data[3];\n";
+        hdr << "extern const uint64_t arr_dmmv_id_" << tname << "_f32_f32_ocp_len[3];\n";
+        if (basename(input_filepath) == "mul_mat_vec.comp") {
+            src << "const void * arr_dmmv_id_"   << tname << "_f32_f32_ocp_data[3] = {mul_mat_vec_id_" << tname << "_f32_f32_ocp_data, mul_mat_vec_id_" << tname << "_f32_f32_ocp_subgroup_data, mul_mat_vec_id_" << tname << "_f32_f32_ocp_subgroup_no_shmem_data};\n";
+            src << "const uint64_t arr_dmmv_id_" << tname << "_f32_f32_ocp_len[3] =  {mul_mat_vec_id_" << tname << "_f32_f32_ocp_len,  mul_mat_vec_id_" << tname << "_f32_f32_ocp_subgroup_len, mul_mat_vec_id_"  << tname << "_f32_f32_ocp_subgroup_no_shmem_len};\n";
+        }
+    }
+#endif
+
     if (input_filepath == "") {
         write_file_if_changed(target_hpp, hdr.str());
     }

ggml/src/gguf.cpp

@@ -1186,6 +1186,11 @@ const char * gguf_get_tensor_name(const struct gguf_context * ctx, int64_t tenso
     return ctx->info[tensor_id].t.name;
 }
 
+const int64_t * gguf_get_tensor_ne(const struct gguf_context * ctx, int64_t tensor_id) {
+    GGML_ASSERT(tensor_id >= 0 && tensor_id < gguf_get_n_tensors(ctx));
+    return ctx->info[tensor_id].t.ne;
+}
+
 enum ggml_type gguf_get_tensor_type(const struct gguf_context * ctx, int64_t tensor_id) {
     GGML_ASSERT(tensor_id >= 0 && tensor_id < gguf_get_n_tensors(ctx));
     return ctx->info[tensor_id].t.type;

gguf-py/gguf/constants.py

@@ -512,6 +512,7 @@ class MODEL_ARCH(IntEnum):
     HUNYUAN_MOE      = auto()
     HUNYUAN_DENSE    = auto()
     HUNYUAN_VL       = auto()
+    HY_V3            = auto()
     SMOLLM3          = auto()
     GPT_OSS          = auto()
     LFM2             = auto()
@@ -1093,6 +1094,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
     MODEL_ARCH.HUNYUAN_MOE:      "hunyuan-moe",
     MODEL_ARCH.HUNYUAN_DENSE:    "hunyuan-dense",
     MODEL_ARCH.HUNYUAN_VL:       "hunyuan_vl",
+    MODEL_ARCH.HY_V3:            "hy_v3",
     MODEL_ARCH.SMOLLM3:          "smollm3",
     MODEL_ARCH.GPT_OSS:          "gpt-oss",
     MODEL_ARCH.LFM2:             "lfm2",
@@ -3936,6 +3938,37 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
     ],
+    MODEL_ARCH.HY_V3: [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.OUTPUT,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_Q,
+        MODEL_TENSOR.ATTN_Q_NORM,
+        MODEL_TENSOR.ATTN_K,
+        MODEL_TENSOR.ATTN_K_NORM,
+        MODEL_TENSOR.ATTN_V,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.FFN_NORM,
+        MODEL_TENSOR.FFN_GATE,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_UP,
+        MODEL_TENSOR.FFN_GATE_INP,
+        MODEL_TENSOR.FFN_EXP_PROBS_B,
+        MODEL_TENSOR.FFN_GATE_EXP,
+        MODEL_TENSOR.FFN_DOWN_EXP,
+        MODEL_TENSOR.FFN_UP_EXP,
+        MODEL_TENSOR.FFN_GATE_SHEXP,
+        MODEL_TENSOR.FFN_DOWN_SHEXP,
+        MODEL_TENSOR.FFN_UP_SHEXP,
+        # NextN/MTP tensors (draft head)
+        MODEL_TENSOR.NEXTN_EH_PROJ,
+        MODEL_TENSOR.NEXTN_EMBED_TOKENS,
+        MODEL_TENSOR.NEXTN_ENORM,
+        MODEL_TENSOR.NEXTN_HNORM,
+        MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
+        MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
+    ],
     MODEL_ARCH.SMOLLM3: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.OUTPUT_NORM,

models/templates/tencent-Hy3.jinja

@@ -0,0 +1,222 @@
+{#- ------------- special token variables ------------- -#}
+{%- set HYTK = ':opensource' %}
+{%- set eos_token = '<｜hy_eos{}｜>'.format(HYTK) %}
+{%- set bos_token = '<｜hy_begin_of_sentence{}｜>'.format(HYTK) %}
+{%- set pad_token = '<｜hy_pad{}｜>'.format(HYTK) %}
+{%- set user_token = '<｜hy_User{}｜>'.format(HYTK) %}
+{%- set assistant_token = '<｜hy_Assistant{}｜>'.format(HYTK) %}
+{%- set think_begin_token = '<think{}>'.format(HYTK) %}
+{%- set think_end_token = '</think{}>'.format(HYTK) %}
+{%- set toolcalls_begin_token = '<tool_calls{}>'.format(HYTK) %}
+{%- set toolcalls_end_token = '</tool_calls{}>'.format(HYTK) %}
+{%- set toolcall_begin_token = '<tool_call{}>'.format(HYTK) %}
+{%- set toolcall_end_token = '</tool_call{}>'.format(HYTK) %}
+{%- set toolsep_token = '<tool_sep{}>'.format(HYTK) %}
+{%- set argkey_begin_token = '<arg_key{}>'.format(HYTK) %}
+{%- set argkey_end_token = '</arg_key{}>'.format(HYTK) %}
+{%- set argvalue_begin_token = '<arg_value{}>'.format(HYTK) %}
+{%- set argvalue_end_token = '</arg_value{}>'.format(HYTK) %}
+{%- set toolresponses_begin_token = '<tool_responses{}>'.format(HYTK) %}
+{%- set toolresponses_end_token = '</tool_responses{}>'.format(HYTK) %}
+{%- set toolresponse_begin_token = '<tool_response{}>'.format(HYTK) %}
+{%- set toolresponse_end_token = '</tool_response{}>'.format(HYTK) %}
+{%- set reasoning_mode_token = '<｜reasoning_mode{}｜>'.format(HYTK) %}
+
+{#- ------------- hyperparameters variables ------------- -#}
+{%- if not add_generation_prompt is defined %}
+    {%- set add_generation_prompt = false %}
+{%- endif %}
+{%- if not preserved_thinking is defined %}
+    {%- if not tools %}
+        {%- set preserved_thinking = false %}
+    {%- else %}
+        {%- set preserved_thinking = true %}
+    {%- endif %}
+{%- endif %}
+{%- if not is_training is defined %}
+    {%- set is_training = false %}
+{%- endif %}
+
+{%- if not reasoning_effort is defined %}
+    {%- set reasoning_effort = 'no_think' %}
+{%- elif reasoning_effort not in ['high', 'low', 'no_think'] %}
+    {%- if reasoning_effort is none %}
+        {{- raise_exception('reasoning_effort error : None, should be no_think/low/high') }}
+    {%- else %}
+        {{- raise_exception('reasoning_effort error : ' + reasoning_effort + ', should be no_think/low/high') }}
+    {%- endif %}
+{%- endif %}
+
+{%- if fallback_strategy is defined and fallback_strategy == 'reasoning_toolcall_retry' %}
+    {%- set reasoning_effort = 'high' %}
+    {%- set add_generation_prompt = false %}
+{%- endif %}
+{%- if not raw_last_assistant is defined %}
+    {%- set raw_last_assistant = false %}
+{%- endif %}
+
+{%- macro visible_text(content) -%}
+    {%- if content is string -%}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping -%}
+        {%- for item in content -%}
+            {%- if item is mapping and item.type == 'text' -%}
+                {{- item.text }}
+            {%- elif item is string -%}
+                {{- item }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- elif content is none -%}
+        {{- '' }}
+    {%- else -%}
+        {{- content }}
+    {%- endif -%}
+{%- endmacro -%}
+
+{%- set ns = namespace(last_user_index=-1) %}
+{%- set sp_ns = namespace(system_prompt='', is_first_sp=true) %}
+{%- for message in messages %}
+    {%- if message['role'] == 'system' %}
+        {%- set sp_ns.system_prompt = sp_ns.system_prompt + visible_text(message['content']) %}
+    {%- endif %}
+    {%- if message['role'] == 'user' %}
+        {%- set ns.last_user_index = loop.index0 %}
+    {%- endif %}
+{%- endfor %}
+{%- if reasoning_effort is defined and reasoning_effort is string and reasoning_effort != '' and not tools %}
+    {%- set sp_ns.system_prompt = sp_ns.system_prompt + reasoning_mode_token + 'reasoning_effort:' + reasoning_effort %}
+{%- endif %}
+{{- bos_token }}
+{{- sp_ns.system_prompt }}
+{%- if tools %}
+    {%- if sp_ns.system_prompt != '' %}
+        {{- '\n\n# Tools\n\nYou may call one or more functions to assist with the user query.' }}
+    {%- else %}
+        {{- '# Tools\n\nYou may call one or more functions to assist with the user query.' }}
+    {%- endif %}
+    {{- '\n\nYou are provided with function signatures within <tools></tools> XML tags:' }}
+    {{- '\n<tools>\n' }}
+    {%- for tool in tools %}
+        {%- if loop.index0 > 0 %}
+            {{- '\n' }}
+        {%- endif %}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- '\n</tools>\n\n' }}
+    {{- 'For function call returns, you should first print ' + toolcalls_begin_token + '\n' }}
+    {{- 'For each function call, you should return object like:\n' }}
+    {{- toolcall_begin_token + '{function-name}' + toolsep_token + '\n' }}
+    {{- argkey_begin_token + '{arg-key-1}' + argkey_end_token + '\n' }}
+    {{- argvalue_begin_token + '{arg-value-1}' + argvalue_end_token + '\n' }}
+    {{- argkey_begin_token + '{arg-key-2}' + argkey_end_token + '\n' }}
+    {{- argvalue_begin_token + '{arg-value-2}' + argvalue_end_token + '\n' }}
+    {{- '...\n' }}
+    {{- toolcall_end_token + '\n' }}
+    {%- if reasoning_effort is defined and reasoning_effort is string and reasoning_effort != '' %}
+        {{- 'At the end of function call returns, you should print ' + toolcalls_end_token + reasoning_mode_token + 'reasoning_effort:' + reasoning_effort }}
+    {%- else %}
+        {{- 'At the end of function call returns, you should print ' + toolcalls_end_token }}
+    {%- endif %}
+{%- endif %}
+
+{%- set prev_ns = namespace(is_tool=false, is_tool_first=true) %}
+{%- set last_ns = namespace(last_is_assistant=false) %}
+{%- for message in messages %}
+    {%- if message['role'] == 'user' %}
+        {%- if prev_ns.is_tool %}
+            {{- toolresponses_end_token }}
+        {%- endif %}
+        {{- user_token + visible_text(message['content']) }}
+        {%- set prev_ns.is_tool = false %}
+    {%- endif %}
+    {%- if message['role'] == 'assistant' %}
+        {%- if is_training %}
+            {%- if 'reasoning_content' in message and message['reasoning_content'] is string %}
+                {%- set rc = message['reasoning_content'] %}
+            {%- elif 'reasoning' in message and message['reasoning'] is string %}
+                {%- set rc = message['reasoning'] %}
+            {%- else %}
+                {%- set rc = none %}
+            {%- endif %}
+            {%- if rc is not none %}
+                {%- set content = think_begin_token + rc + think_end_token + visible_text(message['content']) %}
+            {%- else %}
+                {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %}
+            {%- endif %}
+        {%- else %}
+            {%- if ((preserved_thinking is defined and preserved_thinking) or loop.index0 > ns.last_user_index) %}
+                {%- if 'reasoning_content' in message and message['reasoning_content'] is string %}
+                    {%- set rc = message['reasoning_content'] %}
+                {%- elif 'reasoning' in message and message['reasoning'] is string %}
+                    {%- set rc = message['reasoning'] %}
+                {%- else %}
+                    {%- set rc = none %}
+                {%- endif %}
+                {%- if rc is not none %}
+                    {%- set content = think_begin_token + rc + think_end_token + visible_text(message['content']) %}
+                {%- else %}
+                    {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %}
+                {%- endif %}
+            {%- else %}
+                {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %}
+            {%- endif %}
+        {%- endif %}
+        {%- if prev_ns.is_tool %}
+            {{- toolresponses_end_token }}
+        {%- endif %}
+        {{- assistant_token }}
+        {%- if message['tool_calls'] is defined and message['tool_calls'] %}
+            {%- set prev_ns.is_tool_first = true %}
+            {{- content }}
+            {{- toolcalls_begin_token + '\n' }}
+            {%- for tool in message['tool_calls'] %}
+                {%- set arguments = tool['function']['arguments'] %}
+                {{- toolcall_begin_token + tool['function']['name'] + toolsep_token + '\n' }}
+                {%- for key, value in arguments.items() %}
+                    {{- argkey_begin_token + key + argkey_end_token + '\n' }}
+                    {%- if value is not string %}
+                        {%- set value = value | tojson(ensure_ascii=False) %}
+                    {%- endif %}
+                    {{- argvalue_begin_token + value + argvalue_end_token + '\n' }}
+                {%- endfor %}
+                {{- toolcall_end_token + '\n' }}
+            {%- endfor %}
+            {{- toolcalls_end_token + eos_token }}
+        {%- else %}
+            {%- if loop.last and raw_last_assistant %}
+                {{- visible_text(message['content']) }}
+            {%- elif not loop.last or is_training %}
+                {{- content + eos_token }}
+            {%- else %}
+                {{- content }}
+            {%- endif %}
+        {%- endif %}
+        {%- set prev_ns.is_tool = false %}
+    {%- endif %}
+    {%- if message['role'] == 'tool' %}
+        {%- set prev_ns.is_tool = true %}
+        {%- if prev_ns.is_tool_first %}
+            {{- toolresponses_begin_token + '\n' }}
+            {%- set prev_ns.is_tool_first = false %}
+        {%- endif %}
+        {{- toolresponse_begin_token + '\n' + visible_text(message['content']) + '\n' + toolresponse_end_token + '\n' }}
+    {%- endif %}
+    {%- if loop.last and message['role'] == 'assistant' %}
+        {%- set last_ns.last_is_assistant = true %}
+    {%- endif %}
+
+{%- endfor %}
+{%- if prev_ns.is_tool %}
+    {{- toolresponses_end_token }}
+{%- endif %}
+{%- if add_generation_prompt %}
+    {%- if not last_ns.last_is_assistant %}
+        {%- if reasoning_effort is defined and reasoning_effort in ['low', 'high'] %}
+            {{- assistant_token + think_begin_token }}
+        {%- elif reasoning_effort is defined and reasoning_effort == 'no_think' %}
+            {{- assistant_token + think_begin_token + think_end_token }}
+        {%- else %}
+            {{- assistant_token }}
+        {%- endif %}
+    {%- endif %}
+{%- endif %}

src/llama-arch.cpp

@@ -113,6 +113,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_HUNYUAN_MOE,      "hunyuan-moe"      },
     { LLM_ARCH_HUNYUAN_DENSE,    "hunyuan-dense"    },
     { LLM_ARCH_HUNYUAN_VL,       "hunyuan_vl"       },
+    { LLM_ARCH_HY_V3,            "hy_v3"            },
     { LLM_ARCH_SMOLLM3,          "smollm3"          },
     { LLM_ARCH_OPENAI_MOE,       "gpt-oss"          },
     { LLM_ARCH_LFM2,             "lfm2"             },

src/llama-arch.h

@@ -118,6 +118,7 @@ enum llm_arch {
     LLM_ARCH_HUNYUAN_MOE,
     LLM_ARCH_HUNYUAN_DENSE,
     LLM_ARCH_HUNYUAN_VL,
+    LLM_ARCH_HY_V3,
     LLM_ARCH_SMOLLM3,
     LLM_ARCH_OPENAI_MOE,
     LLM_ARCH_LFM2,

src/llama-model.cpp

@@ -262,6 +262,8 @@ static llama_model * llama_model_mapping(llm_arch arch, const llama_model_params
             return new llama_model_hunyuan_vl(params);
         case LLM_ARCH_HUNYUAN_DENSE:
             return new llama_model_hunyuan_dense(params);
+        case LLM_ARCH_HY_V3:
+            return new llama_model_hy_v3(params);
         case LLM_ARCH_SMOLLM3:
             return new llama_model_smollm3(params);
         case LLM_ARCH_OPENAI_MOE:
@@ -2169,7 +2171,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
                         filter = [&](uint32_t il) { return il >= hparams.n_layer(); };
                     }
 
-                    if (arch == LLM_ARCH_STEP35 && hparams.n_layer_nextn > 0) {
+                    if ((arch == LLM_ARCH_STEP35 || arch == LLM_ARCH_HY_V3) && hparams.n_layer_nextn > 0) {
                         if (params.ctx_type == LLAMA_CONTEXT_TYPE_MTP) {
                             filter = [&](uint32_t il) { return il >= hparams.n_layer(); };
                         } else {
@@ -2525,6 +2527,7 @@ llama_rope_type llama_model_rope_type(const llama_model * model) {
         case LLM_ARCH_JAIS2:
         case LLM_ARCH_OPENAI_MOE:
         case LLM_ARCH_HUNYUAN_DENSE:
+        case LLM_ARCH_HY_V3:
         case LLM_ARCH_LFM2:
         case LLM_ARCH_LFM2MOE:
         case LLM_ARCH_SMALLTHINKER:

src/models/hy-v3.cpp

@@ -0,0 +1,390 @@
+#include "models.h"
+
+void llama_model_hy_v3::load_arch_hparams(llama_model_loader & ml) {
+    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,       hparams.f_norm_rms_eps);
+    ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH,        hparams.n_ff_exp);
+    ml.get_key(LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH, hparams.n_ff_shexp, false);
+    ml.get_key(LLM_KV_EXPERT_GATING_FUNC,                hparams.expert_gating_func, false);
+    ml.get_key(LLM_KV_EXPERT_WEIGHTS_SCALE,              hparams.expert_weights_scale, false);
+    ml.get_key(LLM_KV_EXPERT_WEIGHTS_NORM,               hparams.expert_weights_norm, false);
+
+    // HY V3 uses a sigmoid router with expert selection bias by default
+    if (hparams.expert_gating_func == LLAMA_EXPERT_GATING_FUNC_TYPE_NONE) {
+        hparams.expert_gating_func = LLAMA_EXPERT_GATING_FUNC_TYPE_SIGMOID;
+    }
+
+    // NextN/MTP (HY V3): extra decoder block(s) appended beyond the main stack
+    ml.get_key(LLM_KV_NEXTN_PREDICT_LAYERS, hparams.n_layer_nextn, false);
+    GGML_ASSERT(hparams.n_layer_nextn < hparams.n_layer_all && "n_layer_nextn must be < n_layer_all");
+
+    switch (hparams.n_layer()) {
+        case 48: type = LLM_TYPE_30B_A3B; break;
+        default: type = LLM_TYPE_UNKNOWN;
+    }
+}
+
+void llama_model_hy_v3::load_arch_tensors(llama_model_loader & ml) {
+    LLAMA_LOAD_LOCALS;
+
+    const bool mtp_only = (hparams.n_layer_nextn > 0) && (ml.get_weight("blk.0.attn_norm.weight") == nullptr);
+    // Trunk-only: the GGUF declares MTP layers in metadata but the actual MTP
+    // tensors live in a separate file (e.g. user split target/draft). Mark
+    // MTP tensors NOT_REQUIRED so the trunk loads cleanly.
+    const std::string mtp_probe = "blk." + std::to_string(n_layer) + ".nextn.eh_proj.weight";
+    const bool trunk_only = (hparams.n_layer_nextn > 0) && (ml.get_weight(mtp_probe.c_str()) == nullptr);
+    const int trunk_flags = mtp_only   ? TENSOR_NOT_REQUIRED : 0;
+    const int mtp_flags   = trunk_only ? TENSOR_NOT_REQUIRED : 0;
+
+    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
+
+    output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);
+    output      = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
+    if (output == NULL) {
+        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
+    }
+
+    auto load_block = [&](int i, int flags) {
+        auto & layer = layers[i];
+        const int64_t n_ff_exp   = hparams.n_ff_exp   ? hparams.n_ff_exp   : n_ff / (n_expert_used > 0 ? n_expert_used : 1);
+        const int64_t n_ff_shexp = hparams.n_ff_shexp ? hparams.n_ff_shexp : n_ff_exp;
+
+        layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, flags);
+
+        create_tensor_qkv(layer, i, n_embd, n_embd_head_k * n_head, n_embd_k_gqa, n_embd_v_gqa, flags);
+        layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * n_head, n_embd}, flags);
+
+        layer.attn_q_norm = create_tensor(tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k}, flags);
+        layer.attn_k_norm = create_tensor(tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k}, flags);
+
+        layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, flags);
+
+        // dense FFN (leading dense blocks, first_k_dense_replace)
+        layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED);
+        layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, TENSOR_NOT_REQUIRED);
+        layer.ffn_up   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED);
+
+        // MoE routed experts (sigmoid router + expert selection bias)
+        layer.ffn_gate_inp    = create_tensor(tn(LLM_TENSOR_FFN_GATE_INP,    "weight", i), {n_embd, n_expert}, TENSOR_NOT_REQUIRED);
+        layer.ffn_exp_probs_b = create_tensor(tn(LLM_TENSOR_FFN_EXP_PROBS_B,           i), {n_expert}, TENSOR_NOT_REQUIRED);
+        layer.ffn_down_exps   = create_tensor(tn(LLM_TENSOR_FFN_DOWN_EXPS,   "weight", i), {n_ff_exp, n_embd, n_expert}, TENSOR_NOT_REQUIRED);
+        create_tensor_gate_up_exps(layer, i, n_embd, n_ff_exp, n_expert, TENSOR_NOT_REQUIRED);
+
+        // shared expert (always active, no gate)
+        layer.ffn_gate_shexp = create_tensor(tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, n_ff_shexp}, TENSOR_NOT_REQUIRED);
+        layer.ffn_up_shexp   = create_tensor(tn(LLM_TENSOR_FFN_UP_SHEXP,   "weight", i), {n_embd, n_ff_shexp}, TENSOR_NOT_REQUIRED);
+        layer.ffn_down_shexp = create_tensor(tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {n_ff_shexp, n_embd}, TENSOR_NOT_REQUIRED);
+    };
+
+    for (int i = 0; i < n_layer; ++i) {
+        load_block(i, trunk_flags);
+    }
+
+    // NextN/MTP block(s): a full hy_v3 decoder block plus the NextN projections.
+    for (int i = n_layer; i < n_layer_all; ++i) {
+        auto & layer = layers[i];
+
+        load_block(i, mtp_flags);
+
+        layer.nextn.eh_proj          = create_tensor(tn(LLM_TENSOR_NEXTN_EH_PROJ,          "weight", i), { 2 * n_embd, n_embd }, mtp_flags);
+        layer.nextn.enorm            = create_tensor(tn(LLM_TENSOR_NEXTN_ENORM,            "weight", i), { n_embd },             mtp_flags);
+        layer.nextn.hnorm            = create_tensor(tn(LLM_TENSOR_NEXTN_HNORM,            "weight", i), { n_embd },             mtp_flags);
+        layer.nextn.embed_tokens     = create_tensor(tn(LLM_TENSOR_NEXTN_EMBED_TOKENS,     "weight", i), { n_embd, n_vocab },    TENSOR_NOT_REQUIRED);
+        layer.nextn.shared_head_head = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, "weight", i), { n_embd, n_vocab },    TENSOR_NOT_REQUIRED);
+        // hy_v3 stores the MTP block's trailing final_layernorm here (applied
+        // after the decoder block, before the shared LM head).
+        layer.nextn.shared_head_norm = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, "weight", i), { n_embd },             TENSOR_NOT_REQUIRED);
+    }
+}
+
+std::unique_ptr<llm_graph_context> llama_model_hy_v3::build_arch_graph(const llm_graph_params & params) const {
+    if (params.gtype == LLM_GRAPH_TYPE_DECODER_MTP) {
+        return std::make_unique<graph_mtp>(*this, params);
+    }
+    return std::make_unique<graph>(*this, params);
+}
+
+llama_model_hy_v3::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
+    const int64_t n_embd_head = hparams.n_embd_head_v();
+
+    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());
+    GGML_ASSERT(n_embd_head == n_rot);
+
+    ggml_tensor * cur;
+    ggml_tensor * inpL;
+
+    inpL = build_inp_embd(model.tok_embd);
+    ggml_tensor * inp_pos = build_inp_pos();
+    auto * inp_attn = build_attn_inp_kv();
+    ggml_tensor * inp_out_ids = build_inp_out_ids();
+
+    const float kq_scale = 1.0f / sqrtf(float(n_embd_head));
+
+    // MTP/NextN layers are loaded as extra decoder blocks but not executed in the main pass.
+    for (int il = 0; il < n_layer; ++il) {
+        ggml_tensor * inpSA = inpL;
+
+        cur = build_norm(inpL, model.layers[il].attn_norm, nullptr, LLM_NORM_RMS, il);
+        cb(cur, "attn_norm", il);
+
+        // self-attention
+        {
+            ggml_tensor * rope_factors = model.get_rope_factors(cparams, il);
+
+            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur, n_embd_head, n_head, n_head_kv, il);
+
+            Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, nullptr, LLM_NORM_RMS, il);
+            Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, nullptr, LLM_NORM_RMS, il);
+
+            Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, rope_factors,
+                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow);
+            Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, rope_factors,
+                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow);
+
+            cur = build_attn(inp_attn,
+                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,
+                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, kq_scale, il);
+            cb(cur, "attn_out", il);
+        }
+
+        if (il == n_layer - 1 && inp_out_ids && cparams.embeddings_nextn_masked) {
+            cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
+            inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
+        }
+
+        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
+        cb(ffn_inp, "ffn_inp", il);
+
+        cur = build_norm(ffn_inp, model.layers[il].ffn_norm, nullptr, LLM_NORM_RMS, il);
+        cb(cur, "ffn_norm", il);
+
+        if (model.layers[il].ffn_gate_inp == nullptr) {
+            // dense FFN (leading dense blocks)
+            cur = build_ffn(cur,
+                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   model.layers[il].ffn_up_s,
+                    model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, model.layers[il].ffn_gate_s,
+                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, model.layers[il].ffn_down_s,
+                    nullptr,
+                    LLM_FFN_SILU, LLM_FFN_PAR, il);
+            cb(cur, "ffn_dense_out", il);
+        } else {
+            // MoE routed experts (sigmoid gating + expert selection bias)
+            ggml_tensor * moe_out = build_moe_ffn(cur,
+                    model.layers[il].ffn_gate_inp,
+                    model.layers[il].ffn_up_exps,
+                    model.layers[il].ffn_gate_exps,
+                    model.layers[il].ffn_down_exps,
+                    model.layers[il].ffn_exp_probs_b,
+                    n_expert, n_expert_used,
+                    LLM_FFN_SILU,
+                    hparams.expert_weights_norm,
+                    hparams.expert_weights_scale,
+                    (llama_expert_gating_func_type) hparams.expert_gating_func,
+                    il,
+                    nullptr, model.layers[il].ffn_gate_up_exps,
+                    model.layers[il].ffn_up_exps_s,
+                    model.layers[il].ffn_gate_exps_s,
+                    model.layers[il].ffn_down_exps_s);
+            cb(moe_out, "ffn_moe_out", il);
+
+            // shared expert (always active, no gate)
+            ggml_tensor * sh_out = build_ffn(cur,
+                    model.layers[il].ffn_up_shexp,   nullptr, model.layers[il].ffn_up_shexp_s,
+                    model.layers[il].ffn_gate_shexp, nullptr, model.layers[il].ffn_gate_shexp_s,
+                    model.layers[il].ffn_down_shexp, nullptr, model.layers[il].ffn_down_shexp_s,
+                    nullptr,
+                    LLM_FFN_SILU, LLM_FFN_PAR, il);
+            cb(sh_out, "ffn_shared_out", il);
+
+            cur = ggml_add(ctx0, moe_out, sh_out);
+            cb(cur, "ffn_out", il);
+        }
+
+        cur = ggml_add(ctx0, cur, ffn_inp);
+        cur = build_cvec(cur, il);
+        cb(cur, "l_out", il);
+
+        inpL = cur;
+    }
+
+    cur = build_norm(inpL, model.output_norm, nullptr, LLM_NORM_RMS, -1);
+
+    // Post-final-norm hidden state: what the MTP draft head's hnorm consumes.
+    // vLLM feeds the target model's normed output states, and the MTP layer
+    // itself returns final_layernorm(h), so the chained state is post-norm.
+    cb(cur, "h_nextn", -1);
+    res->t_h_nextn = cur;
+
+    if (!cparams.embeddings_nextn_masked && inp_out_ids) {
+        cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+    }
+
+    cb(cur, "result_norm", -1);
+    res->t_embd = cur;
+
+    cur = build_lora_mm(model.output, cur, model.output_s);
+    cb(cur, "result_output", -1);
+    res->t_logits = cur;
+
+    ggml_build_forward_expand(gf, cur);
+}
+
+// LLM_GRAPH_TYPE_DECODER_MTP draft head for HY V3 (MoE).
+// Semantics mirror vLLM's HYV3MultiTokenPredictorLayer (hy_v3_mtp.py):
+//   enorm(embed) + hnorm(prev_hidden) -> concat(e, h) -> eh_proj ->
+//   hy_v3 decoder block -> final_layernorm (stored as nextn.shared_head_norm) ->
+//   shared LM head (the main model's lm_head; the checkpoint has no separate
+//   MTP head or MTP embeddings).
+llama_model_hy_v3::graph_mtp::graph_mtp(const llama_model & model, const llm_graph_params & params)
+    : llm_graph_context(params) {
+    GGML_ASSERT(hparams.n_layer_nextn > 0 && "HY_V3 MTP requires n_layer_nextn > 0");
+
+    const int64_t n_embd_head = hparams.n_embd_head_v();
+    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());
+    GGML_ASSERT(n_embd_head == n_rot);
+
+    const int il = hparams.n_layer() + cparams.nextn_layer_offset;
+    GGML_ASSERT(cparams.nextn_layer_offset >= 0 &&
+                cparams.nextn_layer_offset < (int) hparams.n_layer_nextn &&
+                "nextn_layer_offset out of range [0, n_layer_nextn)");
+    const auto & layer = model.layers[il];
+
+    GGML_ASSERT(layer.nextn.eh_proj && "MTP block missing nextn.eh_proj");
+    GGML_ASSERT(layer.nextn.enorm   && "MTP block missing nextn.enorm");
+    GGML_ASSERT(layer.nextn.hnorm   && "MTP block missing nextn.hnorm");
+
+    auto inp = std::make_unique<llm_graph_input_embd>(hparams.n_embd);
+
+    inp->tokens = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_tokens);
+    ggml_set_input(inp->tokens);
+
+    inp->embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, hparams.n_embd, n_tokens);
+    ggml_set_input(inp->embd);
+    ggml_set_name(inp->embd, "mtp_h_input");
+
+    ggml_tensor * tok_embd_w = layer.nextn.embed_tokens ? layer.nextn.embed_tokens : model.tok_embd;
+
+    ggml_tensor * h_input  = inp->embd;
+    ggml_tensor * tok_embd = ggml_get_rows(ctx0, tok_embd_w, inp->tokens);
+    cb(tok_embd, "mtp_tok_embd", il);
+
+    res->add_input(std::move(inp));
+
+    ggml_tensor * inp_pos     = build_inp_pos();
+    ggml_tensor * inp_out_ids = build_inp_out_ids();
+    auto * inp_attn           = build_attn_inp_kv();
+
+    ggml_tensor * h_norm = build_norm(h_input, layer.nextn.hnorm, nullptr, LLM_NORM_RMS, il);
+    cb(h_norm, "mtp_hnorm", il);
+
+    ggml_tensor * e_norm = build_norm(tok_embd, layer.nextn.enorm, nullptr, LLM_NORM_RMS, il);
+    cb(e_norm, "mtp_enorm", il);
+
+    ggml_tensor * concat = ggml_concat(ctx0, e_norm, h_norm, /*dim=*/ 0);
+    cb(concat, "mtp_concat", il);
+
+    ggml_tensor * cur = build_lora_mm(layer.nextn.eh_proj, concat);
+    cb(cur, "mtp_eh_proj", il);
+
+    ggml_tensor * inpSA = cur;
+
+    // mtp_block: a full hy_v3 decoder layer (mirrors the trunk graph)
+    cur = build_norm(cur, layer.attn_norm, nullptr, LLM_NORM_RMS, il);
+    cb(cur, "mtp_attn_norm", il);
+
+    {
+        ggml_tensor * rope_factors = model.get_rope_factors(cparams, il);
+
+        auto [Qcur, Kcur, Vcur] = build_qkv(layer, cur, n_embd_head, n_head, n_head_kv, il);
+
+        Qcur = build_norm(Qcur, layer.attn_q_norm, nullptr, LLM_NORM_RMS, il);
+        Kcur = build_norm(Kcur, layer.attn_k_norm, nullptr, LLM_NORM_RMS, il);
+
+        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, rope_factors,
+                n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                ext_factor, attn_factor, beta_fast, beta_slow);
+        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, rope_factors,
+                n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
+                ext_factor, attn_factor, beta_fast, beta_slow);
+
+        const float kq_scale = 1.0f / sqrtf(float(n_embd_head));
+
+        cur = build_attn(inp_attn,
+                layer.wo, layer.wo_b, layer.wo_s,
+                Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, kq_scale, il);
+        cb(cur, "mtp_attn_out", il);
+    }
+
+    ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
+    cb(ffn_inp, "mtp_ffn_inp", il);
+
+    cur = build_norm(ffn_inp, layer.ffn_norm, nullptr, LLM_NORM_RMS, il);
+    cb(cur, "mtp_ffn_norm", il);
+
+    if (layer.ffn_gate_inp == nullptr) {
+        cur = build_ffn(cur,
+                layer.ffn_up,   layer.ffn_up_b,   layer.ffn_up_s,
+                layer.ffn_gate, layer.ffn_gate_b, layer.ffn_gate_s,
+                layer.ffn_down, layer.ffn_down_b, layer.ffn_down_s,
+                nullptr,
+                LLM_FFN_SILU, LLM_FFN_PAR, il);
+        cb(cur, "mtp_ffn_dense_out", il);
+    } else {
+        ggml_tensor * moe_out = build_moe_ffn(cur,
+                layer.ffn_gate_inp,
+                layer.ffn_up_exps,
+                layer.ffn_gate_exps,
+                layer.ffn_down_exps,
+                layer.ffn_exp_probs_b,
+                n_expert, n_expert_used,
+                LLM_FFN_SILU,
+                hparams.expert_weights_norm,
+                hparams.expert_weights_scale,
+                (llama_expert_gating_func_type) hparams.expert_gating_func,
+                il,
+                nullptr, layer.ffn_gate_up_exps,
+                layer.ffn_up_exps_s,
+                layer.ffn_gate_exps_s,
+                layer.ffn_down_exps_s);
+        cb(moe_out, "mtp_ffn_moe_out", il);
+
+        ggml_tensor * sh_out = build_ffn(cur,
+                layer.ffn_up_shexp,   nullptr, layer.ffn_up_shexp_s,
+                layer.ffn_gate_shexp, nullptr, layer.ffn_gate_shexp_s,
+                layer.ffn_down_shexp, nullptr, layer.ffn_down_shexp_s,
+                nullptr,
+                LLM_FFN_SILU, LLM_FFN_PAR, il);
+        cb(sh_out, "mtp_ffn_shared_out", il);
+
+        cur = ggml_add(ctx0, moe_out, sh_out);
+        cb(cur, "mtp_ffn_out", il);
+    }
+
+    cur = ggml_add(ctx0, cur, ffn_inp);
+    cb(cur, "mtp_post_ffn", il);
+
+    // final_layernorm applied after the decoder block, before the shared head.
+    // The post-norm hidden state seeds the next MTP step (matches vLLM, where
+    // HYV3MultiTokenPredictorLayer returns final_layernorm(h)).
+    ggml_tensor * head_norm_w = layer.nextn.shared_head_norm
+            ? layer.nextn.shared_head_norm
+            : model.output_norm;
+    GGML_ASSERT(head_norm_w && "HY_V3 MTP: missing both nextn.shared_head_norm and output_norm");
+    cur = build_norm(cur, head_norm_w, nullptr, LLM_NORM_RMS, -1);
+
+    cb(cur, "h_nextn", -1);
+    res->t_h_nextn = cur;
+
+    cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+    cb(cur, "mtp_shared_head_norm", -1);
+
+    ggml_tensor * head_w = layer.nextn.shared_head_head ? layer.nextn.shared_head_head : model.output;
+    ggml_tensor * head_s = layer.nextn.shared_head_head ? layer.nextn.shared_head_head_s : model.output_s;
+    GGML_ASSERT(head_w && "HY_V3 MTP: missing LM head (nextn.shared_head_head or model.output)");
+    cur = build_lora_mm(head_w, cur, head_s);
+    cb(cur, "result_output", -1);
+
+    res->t_logits = cur;
+    ggml_build_forward_expand(gf, cur);
+}

src/models/minimax-m2.cpp

@@ -60,6 +60,8 @@ llama_model_minimax_m2::graph::graph(const llama_model & model, const llm_graph_
     ggml_tensor * inp_out_ids = build_inp_out_ids();
 
     for (int il = 0; il < n_layer; ++il) {
+        res->t_layer_inp[il] = inpL;
+
         ggml_tensor * inpSA = inpL;
 
         cur = inpL;

src/models/models.h

@@ -1729,6 +1729,22 @@ struct llama_model_hunyuan_moe : public llama_model_base {
     std::unique_ptr<llm_graph_context> build_arch_graph(const llm_graph_params & params) const override;
 };
 
+struct llama_model_hy_v3 : public llama_model_base {
+    llama_model_hy_v3(const struct llama_model_params & params) : llama_model_base(params) {}
+    void load_arch_hparams(llama_model_loader & ml) override;
+    void load_arch_tensors(llama_model_loader & ml) override;
+
+    struct graph : public llm_graph_context {
+        graph(const llama_model & model, const llm_graph_params & params);
+    };
+
+    struct graph_mtp : public llm_graph_context {
+        graph_mtp(const llama_model & model, const llm_graph_params & params);
+    };
+
+    std::unique_ptr<llm_graph_context> build_arch_graph(const llm_graph_params & params) const override;
+};
+
 
 struct llama_model_hunyuan_vl : public llama_model_base {
     llama_model_hunyuan_vl(const struct llama_model_params & params) : llama_model_base(params) {}

tests/CMakeLists.txt

@@ -239,7 +239,6 @@ if (NOT LLAMA_SANITIZE_ADDRESS AND NOT GGML_SCHED_NO_REALLOC)
   # TODO: repair known memory leaks
   llama_build_and_test(test-opt.cpp)
 endif()
-llama_build_and_test(test-gguf.cpp)
 llama_build_and_test(test-backend-ops.cpp)
 
 llama_build_and_test(test-model-load-cancel.cpp LABEL "model")
@@ -299,11 +298,15 @@ get_filename_component(TEST_TARGET test-c.c NAME_WE)
 add_executable(${TEST_TARGET} test-c.c)
 target_link_libraries(${TEST_TARGET} PRIVATE llama)
 
-llama_build_and_test(test-alloc.cpp)
-target_include_directories(test-alloc PRIVATE ${PROJECT_SOURCE_DIR}/ggml/src)
+if (NOT LLAMA_USE_SYSTEM_GGML)
+    # Needs non-public ggml-impl.h
+    llama_build_and_test(test-gguf.cpp)
+
+    # Needs non-public ggml{,-backend}-impl.h
+    llama_build_and_test(test-alloc.cpp)
+endif()
 
 llama_build(test-export-graph-ops.cpp)
-target_include_directories(test-export-graph-ops PRIVATE ${PROJECT_SOURCE_DIR}/ggml/src)
 if (TARGET gguf-model-data)
     target_link_libraries(test-export-graph-ops PRIVATE gguf-model-data)
     target_compile_definitions(test-export-graph-ops PRIVATE LLAMA_HF_FETCH)

tests/test-alloc.cpp

@@ -1,8 +1,8 @@
-#include <ggml-alloc.h>
-#include <ggml-backend-impl.h>
-#include <ggml-cpp.h>
-#include <ggml-impl.h>
-#include <ggml.h>
+#include "ggml-alloc.h"
+#include "../ggml/src/ggml-backend-impl.h"
+#include "ggml-cpp.h"
+#include "../ggml/src/ggml-impl.h"
+#include "ggml.h"
 
 #include <algorithm>
 #include <exception>

tests/test-backend-ops.cpp

@@ -15,10 +15,10 @@
 // ##############################
 
 
-#include <ggml.h>
-#include <ggml-alloc.h>
-#include <ggml-backend.h>
-#include <ggml-cpp.h>
+#include "ggml.h"
+#include "ggml-alloc.h"
+#include "ggml-backend.h"
+#include "ggml-cpp.h"
 
 #include <algorithm>
 #include <atomic>

tests/test-chat-auto-parser.cpp

@@ -1944,6 +1944,9 @@ static void test_role_markers_all_templates(testing & t) {
         // MiniMax M2: ]~b]{user|ai}
         { "MiniMax-M2.jinja",                                "]~b]user",               "]~b]ai"                     },
 
+        // HunYuan V3: <｜hy_User:opensource｜> / <｜hy_Assistant:opensource｜>
+        { "tencent-Hy3.jinja",                               "<｜hy_User:opensource｜>", "<｜hy_Assistant:opensource｜>" },
+
         // Nemotron Nano v2: <SPECIAL_11>{User|Assistant}; assistant marker
         // is followed by a prefilled <think> block that gets included.
         { "NVIDIA-Nemotron-Nano-v2.jinja",                   "<SPECIAL_11>User",       "<SPECIAL_11>Assistant" },

tests/test-gguf.cpp

@@ -662,6 +662,13 @@ static bool handcrafted_check_tensors(const gguf_context * gguf_ctx, const unsig
             if (gguf_get_tensor_type(gguf_ctx, id) != type) {
                 ok = false;
             }
+
+            const int64_t * ne = gguf_get_tensor_ne(gguf_ctx, id);
+            for (int j = 0; j < GGML_MAX_DIMS; ++j) {
+                if (ne[j] != shape[j]) {
+                    ok = false;
+                }
+            }
         } else {
             ok = false;
             continue;

tests/test-jinja.cpp

@@ -1376,6 +1376,36 @@ static void test_string_methods(testing & t) {
         "bXnXna"
     );
 
+    test_template(t, "string.format() auto numbering",
+        "{{ '<{}|{}>'.format(s, 42) }}",
+        {{"s", "hello"}},
+        "<hello|42>"
+    );
+
+    test_template(t, "string.format() manual numbering",
+        "{{ '{1}-{0}-{1}'.format('a', 'b') }}",
+        json::object(),
+        "b-a-b"
+    );
+
+    test_template(t, "string.format() named fields",
+        "{{ '{name} is {age}'.format(name='Bob', age=7) }}",
+        json::object(),
+        "Bob is 7"
+    );
+
+    test_template(t, "string.format() escaped braces",
+        "{{ '{{}} {} {{x}}'.format('mid') }}",
+        json::object(),
+        "{} mid {x}"
+    );
+
+    test_template(t, "string.format() no fields",
+        "{{ 'plain'.format() }}",
+        json::object(),
+        "plain"
+    );
+
     test_template(t, "undefined|capitalize",
         "{{ arr|capitalize }}",
         json::object(),

tests/test-llama-archs.cpp

@@ -346,6 +346,7 @@ static bool moe_mandatory(const llm_arch arch) {
         case LLM_ARCH_ERNIE4_5:
         case LLM_ARCH_ERNIE4_5_MOE:
         case LLM_ARCH_HUNYUAN_MOE:
+        case LLM_ARCH_HY_V3:
         case LLM_ARCH_OPENAI_MOE:
         case LLM_ARCH_LFM2MOE:
         case LLM_ARCH_SMALLTHINKER: