llama: fix magic number of 999 for GPU layers (#18266 )

* llama: fix magic number of 999 for GPU layers * use strings for -ngl, -ngld * enacapsulate n_gpu_layers, split_mode
ggml-cuda: Use same regex for GGML_NATIVE=OFF (#18407 )
2026-07-04 19:45:57 +02:00 · 2025-12-27 20:18:35 +01:00 · 2025-12-27 19:56:27 +08:00 · 2025-12-27 09:59:19 +01:00 · 2025-12-27 09:56:04 +01:00 · 2025-12-26 16:12:58 -06:00
28 changed files with 587 additions and 320 deletions
@@ -2137,11 +2137,18 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
            }
        }
    ).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_N_CPU_MOE_DRAFT"));
+    GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0
    add_opt(common_arg(
        {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N",
-        string_format("max. number of layers to store in VRAM (default: %d)", params.n_gpu_layers),
-        [](common_params & params, int value) {
-            params.n_gpu_layers = value;
+        string_format("max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: %s)", params.n_gpu_layers == -1 ? "auto" : "all"),
+        [](common_params & params, const std::string & value) {
+            if (value == "auto") {
+                params.n_gpu_layers = -1;
+            } else if (value == "all") {
+                params.n_gpu_layers = -2;
+            } else {
+                params.n_gpu_layers = std::stoi(value);
+            }
            if (!llama_supports_gpu_offload()) {
                fprintf(stderr, "warning: no usable GPU found, --gpu-layers option will be ignored\n");
                fprintf(stderr, "warning: one possible reason is that llama.cpp was compiled without GPU support\n");
@@ -3175,11 +3182,19 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
            params.speculative.devices = parse_device_list(value);
        }
    ).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
+    GGML_ASSERT(params.speculative.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0
    add_opt(common_arg(
        {"-ngld", "--gpu-layers-draft", "--n-gpu-layers-draft"}, "N",
-        "number of layers to store in VRAM for the draft model",
-        [](common_params & params, int value) {
-            params.speculative.n_gpu_layers = value;
+        string_format("max. number of draft model layers to store in VRAM, either an exact number, 'auto', or 'all' (default: %s)",
+            params.speculative.n_gpu_layers == -1 ? "auto" : "all"),
+        [](common_params & params, const std::string & value) {
+            if (value == "auto") {
+                params.speculative.n_gpu_layers = -1;
+            } else if (value == "all") {
+                params.speculative.n_gpu_layers = -2;
+            } else {
+                params.speculative.n_gpu_layers = std::stoi(value);
+            }
            if (!llama_supports_gpu_offload()) {
                fprintf(stderr, "warning: no usable GPU found, --gpu-layers-draft option will be ignored\n");
                fprintf(stderr, "warning: one possible reason is that llama.cpp was compiled without GPU support\n");
@@ -1341,10 +1341,7 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
        mparams.devices = params.devices.data();
    }

-    if (params.n_gpu_layers != -1) {
-        mparams.n_gpu_layers = params.n_gpu_layers;
-    }
-
+    mparams.n_gpu_layers    = params.n_gpu_layers;
    mparams.main_gpu        = params.main_gpu;
    mparams.split_mode      = params.split_mode;
    mparams.tensor_split    = params.tensor_split;
@@ -329,7 +329,7 @@ struct common_params {
    // offload params
    std::vector<ggml_backend_dev_t> devices; // devices to use for offloading

-    int32_t n_gpu_layers       = -1;               // number of layers to store in VRAM (-1 - use default)
+    int32_t n_gpu_layers       = -1;               // number of layers to store in VRAM, -1 is auto, <= -2 is all
    int32_t main_gpu           = 0;                // the GPU that is used for scratch and small tensors
    float   tensor_split[128]  = {0};              // how split tensors should be distributed across GPUs
    bool    fit_params         = true;             // whether to fit unset model/context parameters to free device memory
@@ -61,7 +61,7 @@ if (CUDAToolkit_FOUND)
        set(CMAKE_CUDA_ARCHITECTURES ${PROCESSED_ARCHITECTURES})
    else()
        foreach(ARCH ${CMAKE_CUDA_ARCHITECTURES})
-            if(ARCH MATCHES "^12[0-9]$")
+            if(ARCH MATCHES "^12[0-9](-real|-virtual)?$")
                message(FATAL_ERROR "Compute capability ${ARCH} used, use ${ARCH}a or ${ARCH}f for Blackwell specific optimizations")
            endif()
        endforeach()
@@ -651,7 +651,7 @@ struct vk_device_struct {
    vk_pipeline pipeline_add_id_f32;

    vk_pipeline pipeline_concat_f32, pipeline_concat_f16, pipeline_concat_i32;
-    vk_pipeline pipeline_upscale_nearest_f32, pipeline_upscale_bilinear_f32, pipeline_upscale_bicubic_f32;
+    vk_pipeline pipeline_upscale_nearest_f32, pipeline_upscale_bilinear_f32, pipeline_upscale_bicubic_f32, pipeline_upscale_bilinear_antialias_f32;
    vk_pipeline pipeline_scale_f32;
    vk_pipeline pipeline_sqr_f32;
    vk_pipeline pipeline_sqrt_f32;
@@ -763,6 +763,7 @@ struct vk_device_struct {
    std::map<vk_fa_pipeline_state, vk_pipeline> pipeline_flash_attn_f32_f16[GGML_TYPE_COUNT];

    vk_pipeline pipeline_flash_attn_split_k_reduce;
+    vk_pipeline pipeline_count_experts;

    // [2] is for whether to take n_experts from spec constant (0) or push constant (1)
    vk_pipeline pipeline_topk_moe[num_topk_moe_pipelines][TOPK_MOE_COUNT][2];
@@ -1004,6 +1005,14 @@ struct vk_op_push_constants {
    float param4;
 };

+struct vk_op_count_experts_push_constants {
+    uint32_t ne00;
+    uint32_t ne01;
+    uint32_t nb00;
+    uint32_t nb01;
+    uint32_t a_offset;
+};
+
 struct vk_op_glu_push_constants {
    uint32_t N;
    uint32_t ne00;
@@ -1192,6 +1201,7 @@ struct vk_op_diag_mask_push_constants {
 struct vk_op_rope_push_constants {
    uint32_t rope_mode;
    uint32_t ncols;
+    uint32_t nrows;
    uint32_t n_dims;
    float freq_scale;
    uint32_t p_delta_rows;
@@ -1564,7 +1574,7 @@ class vk_perf_logger {
                total_op_times += time;
            }
            std::cerr << t.first << ": " << t.second.size() << " x " << (total_op_times / t.second.size() / 1000.0)
-                      << " us";
+                      << " us = " << (total_op_times / 1000.0) << " us";

            // If we have as many flops entries as timing entries for the op, then compute and log the flops/S.
            auto it = flops.find(t.first);
@@ -2829,9 +2839,9 @@ static void ggml_vk_load_shaders(vk_device& device) {
        s_mmq_wg_denoms_k = { 32,  64,  1 };

        // spec constants and tile sizes for quant matmul_id
-        l_warptile_mmqid = { 256, 128, 128, 16, 1, device->subgroup_size };
-        m_warptile_mmqid = { 256, 128, 64, 16, 0, device->subgroup_size };
-        s_warptile_mmqid = { 256, 128, 64, 16, 0, device->subgroup_size };
+        l_warptile_mmqid = { 256, 128, 128, 32, 1, device->subgroup_size };
+        m_warptile_mmqid = { 256, 128, 64, 32, 0, device->subgroup_size };
+        s_warptile_mmqid = { 256, 128, 64, 32, 0, device->subgroup_size };
        l_mmqid_wg_denoms = { 128, 128, 1 };
        m_mmqid_wg_denoms = { 128, 64, 1 };
        s_mmqid_wg_denoms = { 128, 64, 1 };
@@ -3067,17 +3077,19 @@ static void ggml_vk_load_shaders(vk_device& device) {
 #endif
 #undef CREATE_FA

+    const int mul_mat_id_param_count = 5;
+
 #if defined(VK_NV_cooperative_matrix2) && defined(GGML_VULKAN_COOPMAT2_GLSLC_SUPPORT)
    if (device->coopmat2) {

        // Create 6 variants, {s,m,l}x{unaligned,aligned}
 #define CREATE_MM(PIPELINE_NAME, NAMELC, F16ACC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT) \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1);   \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1);   \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1);   \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_l, #NAMELC #F16ACC "_aligned_l", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, l_align);   \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_m, #NAMELC #F16ACC "_aligned_m", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, m_align);   \
-        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1, true);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1, true);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _cm2_len, NAMELC ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1, true);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_l, #NAMELC #F16ACC "_aligned_l", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, l_align, true);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_m, #NAMELC #F16ACC "_aligned_m", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, m_align, true);   \
+        ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _cm2_len, NAMELC ## _aligned ## F16ACC ## _cm2_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align, true);   \

        // Create 2 variants, {f16,f32} accumulator
 #define CREATE_MM2(PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT) \
@@ -3113,32 +3125,32 @@ static void ggml_vk_load_shaders(vk_device& device) {

        GGML_ASSERT(device->subgroup_ballot);

-        CREATE_MM2(pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile, vk_mat_mat_id_push_constants, 4)
+        CREATE_MM2(pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile, vk_mat_mat_id_push_constants, 5)
 #if defined(GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
        if (device->coopmat_bf16_support) {
-            CREATE_MM(pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, 4)
+            CREATE_MM(pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, 5)
        }
 #endif
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f16,  mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
-        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, 4)
-        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, 4)
-        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, 4)
-        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, 4)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f16,  mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f16,   mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        CREATE_MM2(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f16, mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 5)
+        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)
 #undef CREATE_MM
 #undef CREATE_MM2
    } else
@@ -3227,35 +3239,35 @@ static void ggml_vk_load_shaders(vk_device& device) {

        GGML_ASSERT(device->subgroup_ballot);

-        CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_subgroup_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
+        CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_subgroup_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id);
 #if defined(GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
        if (device->coopmat_bf16_support) {
-            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
+            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id);
        }
 #endif

-        CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
-        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, 4, _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, 4, _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, 4, _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, 4, _id);
+        CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f32,  mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f32,   mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f32, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id);
+        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);
 #undef CREATE_MM2
 #undef CREATE_MM
    } else
@@ -3340,91 +3352,91 @@ static void ggml_vk_load_shaders(vk_device& device) {
 #endif

        if (device->subgroup_ballot && device->subgroup_require_full_support && subgroup_min_size_16) {
-            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_subgroup_f16_f32, wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile_id, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_subgroup_f16, wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_subgroup_f16_f32, wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile_id, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);

-            CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            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_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            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_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            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_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_subgroup_iq1_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_subgroup_iq1_m_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_subgroup_iq2_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_subgroup_iq2_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_subgroup_iq2_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_subgroup_iq3_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            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_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            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_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            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_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);

 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
            if (device->integer_dot_product) {
-                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);

-                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_subgroup_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_subgroup_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);

-                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
-                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
-                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
-                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
-                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
            }
 #endif
        } else {
-            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, 4, _id, 0);
+            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);

-            CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_q4_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_q4_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_q5_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_q5_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_q8_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_q2_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_q3_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_q4_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_q5_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_q6_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_iq1_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_iq1_m_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_iq2_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_iq2_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_iq2_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_iq3_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S],   matmul_id_iq3_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0], matmul_id_q4_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1], matmul_id_q4_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0], matmul_id_q5_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1], matmul_id_q5_1_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0], matmul_id_q8_0_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K], matmul_id_q2_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K], matmul_id_q3_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K], matmul_id_q4_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K], matmul_id_q5_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K], matmul_id_q6_k_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S],   matmul_id_iq1_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M],   matmul_id_iq1_m_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS], matmul_id_iq2_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS],  matmul_id_iq2_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S],   matmul_id_iq2_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS], matmul_id_iq3_xxs_f32, mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S],   matmul_id_iq3_s_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);

 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
            if (device->integer_dot_product) {
-                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);

-                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);

-                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
-                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
            }
 #endif
        }
@@ -3501,57 +3513,57 @@ static void ggml_vk_load_shaders(vk_device& device) {
 #endif

        if (device->subgroup_ballot && device->subgroup_require_full_support && subgroup_min_size_16) {
-            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16.f32acc, matmul_id_subgroup_f16, , wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16_f32.f32acc, matmul_id_subgroup_f16_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, 4, _id, mul_mat_subgroup_size_16);
-            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile_id, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_subgroup_f32_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16.f32acc, matmul_id_subgroup_f16, , wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16_f32.f32acc, matmul_id_subgroup_f16_f32, , wg_denoms, warptile_id, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);
+            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_subgroup_bf16, , wg_denoms, warptile_id, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size_16);

-            CREATE_MM(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f32acc, matmul_id_subgroup_q4_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f32acc, matmul_id_subgroup_q4_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f32acc, matmul_id_subgroup_q5_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f32acc, matmul_id_subgroup_q5_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f32acc, matmul_id_subgroup_q8_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f32acc, matmul_id_subgroup_q2_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f32acc, matmul_id_subgroup_q3_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f32acc, matmul_id_subgroup_q4_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f32acc, matmul_id_subgroup_q5_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_subgroup_q6_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S].f32acc,   matmul_id_subgroup_iq1_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M].f32acc,   matmul_id_subgroup_iq1_m_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f32acc, matmul_id_subgroup_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f32acc,  matmul_id_subgroup_iq2_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f32acc,   matmul_id_subgroup_iq2_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f32acc, matmul_id_subgroup_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f32acc,   matmul_id_subgroup_iq3_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS].f32acc,  matmul_id_subgroup_iq4_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc,  matmul_id_subgroup_iq4_nl_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
-            CREATE_MM(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4].f32acc,   matmul_id_subgroup_mxfp4_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f32acc, matmul_id_subgroup_q4_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f32acc, matmul_id_subgroup_q4_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f32acc, matmul_id_subgroup_q5_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f32acc, matmul_id_subgroup_q5_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f32acc, matmul_id_subgroup_q8_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f32acc, matmul_id_subgroup_q2_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f32acc, matmul_id_subgroup_q3_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f32acc, matmul_id_subgroup_q4_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f32acc, matmul_id_subgroup_q5_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_subgroup_q6_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S].f32acc,   matmul_id_subgroup_iq1_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M].f32acc,   matmul_id_subgroup_iq1_m_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f32acc, matmul_id_subgroup_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f32acc,  matmul_id_subgroup_iq2_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f32acc,   matmul_id_subgroup_iq2_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f32acc, matmul_id_subgroup_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f32acc,   matmul_id_subgroup_iq3_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS].f32acc,  matmul_id_subgroup_iq4_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc,  matmul_id_subgroup_iq4_nl_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
+            CREATE_MM(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4].f32acc,   matmul_id_subgroup_mxfp4_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, mul_mat_subgroup_size);
        } else {
-            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16.f32acc, matmul_id_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16_f32.f32acc, matmul_id_f16_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, 4, _id, 0);
+            CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16.f32acc, matmul_id_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16_f32.f32acc, matmul_id_f16_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);

-            CREATE_MM(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f32acc, matmul_id_q4_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f32acc, matmul_id_q4_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f32acc, matmul_id_q5_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f32acc, matmul_id_q5_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f32acc, matmul_id_q8_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f32acc, matmul_id_q2_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f32acc, matmul_id_q3_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f32acc, matmul_id_q4_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f32acc, matmul_id_q5_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_q6_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S].f32acc,   matmul_id_iq1_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M].f32acc,   matmul_id_iq1_m_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f32acc, matmul_id_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f32acc,  matmul_id_iq2_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f32acc,   matmul_id_iq2_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f32acc, matmul_id_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f32acc,   matmul_id_iq3_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS].f32acc,  matmul_id_iq4_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc,  matmul_id_iq4_nl_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
-            CREATE_MM(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4].f32acc,   matmul_id_mxfp4_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
+            CREATE_MM(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f32acc, matmul_id_q4_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f32acc, matmul_id_q4_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f32acc, matmul_id_q5_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f32acc, matmul_id_q5_1_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f32acc, matmul_id_q8_0_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f32acc, matmul_id_q2_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f32acc, matmul_id_q3_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f32acc, matmul_id_q4_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f32acc, matmul_id_q5_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_q6_k_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ1_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_S].f32acc,   matmul_id_iq1_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ1_M,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ1_M].f32acc,   matmul_id_iq1_m_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ2_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f32acc, matmul_id_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ2_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f32acc,  matmul_id_iq2_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ2_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f32acc,   matmul_id_iq2_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ3_XXS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f32acc, matmul_id_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ3_S,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f32acc,   matmul_id_iq3_s_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS].f32acc,  matmul_id_iq4_xs_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc,  matmul_id_iq4_nl_f32,  , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
+            CREATE_MM(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4].f32acc,   matmul_id_mxfp4_f32,   , mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
        }
    }
    // reusing CREATE_MM from the fp32 path
@@ -3570,7 +3582,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
        s_wg_denoms = { 32,  32, 1 };

        CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_bf16, matmul_bf16, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, , 0);
-        CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, 4, _id, 0);
+        CREATE_MM(GGML_TYPE_BF16, pipeline_matmul_id_bf16, matmul_id_bf16, , wg_denoms, warptile, vk_mat_mat_id_push_constants, mul_mat_id_param_count, _id, 0);
    }
 #undef CREATE_MM

@@ -3955,6 +3967,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
    ggml_vk_create_pipeline(device, device->pipeline_upscale_nearest_f32, "upscale_f32", upscale_f32_len, upscale_f32_data, "main", 2, sizeof(vk_op_upscale_push_constants), {512, 1, 1}, {GGML_SCALE_MODE_NEAREST}, 1);
    ggml_vk_create_pipeline(device, device->pipeline_upscale_bilinear_f32, "upscale_f32", upscale_f32_len, upscale_f32_data, "main", 2, sizeof(vk_op_upscale_push_constants), {512, 1, 1}, {GGML_SCALE_MODE_BILINEAR}, 1);
    ggml_vk_create_pipeline(device, device->pipeline_upscale_bicubic_f32, "upscale_f32", upscale_f32_len, upscale_f32_data, "main", 2, sizeof(vk_op_upscale_push_constants), {512, 1, 1}, {GGML_SCALE_MODE_BICUBIC}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_upscale_bilinear_antialias_f32, "upscale_f32", upscale_f32_len, upscale_f32_data, "main", 2, sizeof(vk_op_upscale_push_constants), {512, 1, 1}, {GGML_SCALE_MODE_BILINEAR | GGML_SCALE_FLAG_ANTIALIAS}, 1);

    ggml_vk_create_pipeline(device, device->pipeline_scale_f32, "scale_f32", scale_f32_len, scale_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1);

@@ -4126,6 +4139,8 @@ static void ggml_vk_load_shaders(vk_device& device) {

    ggml_vk_create_pipeline(device, device->pipeline_count_equal_i32, "count_equal_i32", count_equal_i32_len, count_equal_i32_data, "main", 3, sizeof(vk_op_push_constants), {512, 1, 1}, { device->subgroup_size }, 1);

+    ggml_vk_create_pipeline(device, device->pipeline_count_experts, "count_experts", count_experts_len, count_experts_data, "main", 2, sizeof(vk_op_count_experts_push_constants), {1, 1, 1}, {}, 1, true);
+
    for (auto &s : device->pipeline_solve_tri_f32) {
        const vk_solve_tri_pipeline_state &state = s.first;

@@ -6523,18 +6538,18 @@ static uint32_t ggml_vk_guess_matmul_id_pipeline_align(ggml_backend_vk_context *

 static void ggml_vk_matmul_id(
        ggml_backend_vk_context * ctx, vk_context& subctx, vk_pipeline& pipeline,
-        vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& ids,
+        vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& ids, const vk_subbuffer & expert_count_buf,
        uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d,
        uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d,
        uint32_t n_as, uint32_t nei0, uint32_t nei1, uint32_t nbi1, uint32_t ne11,
        uint32_t padded_n) {
-    VK_LOG_DEBUG("ggml_vk_matmul_id(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), d: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), ids: (" << ids.buffer->buffer << ", " << ids.offset << ", " << ids.size << "), " <<
+    VK_LOG_DEBUG("ggml_vk_matmul_id(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), d: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), ids: (" << ids.buffer->buffer << ", " << ids.offset << ", " << ids.size << "), expert_count: (" << expert_count_buf.buffer->buffer << ", " << expert_count_buf.offset << ", " << expert_count_buf.size << "), " <<
        "m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", " <<
        "batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ", " <<
        "n_as: " << n_as << ", nei0: " << nei0 << ", nei1: " << nei1 << ", nbi1: " << nbi1 << ", ne11: " << ne11 << ")");
    const vk_mat_mat_id_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, batch_stride_a, batch_stride_b, batch_stride_d,
                                              nei0, nei1, nbi1, ne11, padded_n };
-    ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, d, ids }, pc, { m, nei1, n_as });
+    ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, d, ids, expert_count_buf }, pc, { m, nei1, n_as });
 }

 static bool ggml_vk_dim01_contiguous(const ggml_tensor * tensor) {
@@ -7517,6 +7532,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
    const uint64_t nei0 = ids->ne[0];
    const uint64_t nei1 = ids->ne[1];

+    const uint32_t nbi0 = ids->nb[0];
    const uint32_t nbi1 = ids->nb[1];
    const uint32_t nbi2 = ids->nb[2];

@@ -7624,6 +7640,9 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
    if (quantize_y) {
        to_q8_1 = ggml_vk_get_quantize_pipeline(ctx, GGML_TYPE_Q8_1);
    }
+    vk_pipeline count_experts = ctx->device->pipeline_count_experts;
+
+    uint32_t expert_count_size = sizeof(uint32_t) * n_as;

    {
        if (
@@ -7639,6 +7658,10 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
            ctx->prealloc_size_y = y_sz;
            ggml_vk_preallocate_buffers(ctx, subctx);
        }
+        if (ctx->prealloc_size_split_k < expert_count_size) {
+            ctx->prealloc_size_split_k = expert_count_size;
+            ggml_vk_preallocate_buffers(ctx, subctx);
+        }

        // Request descriptor sets
        ggml_pipeline_request_descriptor_sets(ctx, pipeline, 1);
@@ -7651,6 +7674,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
        if (quantize_y) {
            ggml_pipeline_request_descriptor_sets(ctx, to_q8_1, 1);
        }
+        ggml_pipeline_request_descriptor_sets(ctx, count_experts, 1);
    }

    vk_buffer d_D = dst_buf_ctx->dev_buffer;
@@ -7700,6 +7724,20 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
            ggml_vk_sync_buffers(ctx, subctx);
        }
    }
+    // Count how many times each expert is used
+    vk_subbuffer expert_count_buf = ggml_vk_subbuffer(ctx, ctx->prealloc_split_k, 0);
+    if (ctx->prealloc_split_k_need_sync) {
+        ggml_vk_sync_buffers(ctx, subctx);
+    }
+    {
+        const std::vector<uint32_t> pc = { (uint32_t)nei0,
+                                           (uint32_t)nei1,
+                                           (uint32_t)(nbi0 / ggml_type_size(ids->type)),
+                                           (uint32_t)(nbi1 / ggml_type_size(ids->type)),
+                                           (uint32_t)(get_misalign_bytes(ctx, ids) / ggml_type_size(ids->type)) };
+        ggml_vk_dispatch_pipeline(ctx, subctx, count_experts,
+            { vk_subbuffer{ d_ids, ids_buf_offset, ids_sz }, expert_count_buf }, pc, { (uint32_t)n_as, 1, 1});
+    }

    if (x_non_contig) {
        ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, ggml_vk_subbuffer(ctx, d_Qx, qx_buf_offset), ggml_vk_subbuffer(ctx, d_X, 0));
@@ -7707,7 +7745,6 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
        const std::vector<uint32_t> pc = { (uint32_t)ne01, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)(ggml_nelements(src0)) };
        ggml_vk_dispatch_pipeline(ctx, subctx, to_fp16_vk_0,
            { vk_subbuffer{ d_Qx, qx_buf_offset, qx_sz }, vk_subbuffer{ d_X, 0, x_sz } }, pc, { (uint32_t)x_ne, 1, 1});
-        ggml_vk_sync_buffers(ctx, subctx);
    }
    if (y_non_contig) {
        if (ctx->prealloc_y_last_pipeline_used != to_fp16_vk_1.get() ||
@@ -7731,6 +7768,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
            ctx->prealloc_y_last_tensor_used = src1;
        }
    }
+    ggml_vk_sync_buffers(ctx, subctx);

    uint32_t stride_batch_x = ne00*ne01;
    uint32_t stride_batch_y = ne10*ne11;
@@ -7747,7 +7785,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
    ggml_vk_matmul_id(
        ctx, subctx, pipeline,
        { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz },
-        { d_D, d_buf_offset, d_sz }, { d_ids, ids_buf_offset, ids_sz },
+        { d_D, d_buf_offset, d_sz }, { d_ids, ids_buf_offset, ids_sz }, expert_count_buf,
        ne01, ne21, ne10, ne10, ne10, ne01,
        stride_batch_x, stride_batch_y, ne20*ne21,
        n_as, nei0, nei1, nbi1 / ggml_type_size(ids->type), ne11, padded_n
@@ -7759,6 +7797,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
    if (y_non_contig || quantize_y) {
        ctx->prealloc_y_need_sync = true;
    }
+    ctx->prealloc_split_k_need_sync = true;
 }

 static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_context& subctx, const struct ggml_cgraph * cgraph, int node_idx) {
@@ -8432,7 +8471,7 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
        return nullptr;
    case GGML_OP_UPSCALE:
        if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
-            ggml_scale_mode mode = (ggml_scale_mode)(ggml_get_op_params_i32(dst, 0) & 0xFF);
+            uint32_t mode = (ggml_get_op_params_i32(dst, 0) & (0xFF | GGML_SCALE_FLAG_ANTIALIAS));
            switch (mode) {
                case GGML_SCALE_MODE_NEAREST:
                    return ctx->device->pipeline_upscale_nearest_f32;
@@ -8440,6 +8479,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
                    return ctx->device->pipeline_upscale_bilinear_f32;
                case GGML_SCALE_MODE_BICUBIC:
                    return ctx->device->pipeline_upscale_bicubic_f32;
+                case GGML_SCALE_MODE_BILINEAR | GGML_SCALE_FLAG_ANTIALIAS:
+                    return ctx->device->pipeline_upscale_bilinear_antialias_f32;
                default:
                    return nullptr;
            }
@@ -9090,10 +9131,20 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
            elements = { num_groups * (uint32_t)src0->ne[3], 1, 1 };
        } break;
    case GGML_OP_DIAG_MASK_INF:
-    case GGML_OP_ROPE:
-    case GGML_OP_ROPE_BACK:
        elements = { (uint32_t)ggml_nrows(src0), (uint32_t)ne00, 1 };
        break;
+    case GGML_OP_ROPE:
+    case GGML_OP_ROPE_BACK:
+        {
+            uint32_t nrows = (uint32_t)ggml_nrows(src0);
+            uint32_t z = 1;
+            if (nrows > ctx->device->properties.limits.maxComputeWorkGroupCount[0]) {
+                z = CEIL_DIV(nrows, 32768);
+                nrows = 32768;
+            }
+            elements = { nrows, (uint32_t)ne00, z };
+
+        } break;
    case GGML_OP_GET_ROWS:
        elements = { (uint32_t)ne00, (uint32_t)ne10, (uint32_t)(ne11 * ne12) };
        elements[1] = std::min(elements[1], ctx->device->properties.limits.maxComputeWorkGroupCount[1]);
@@ -10021,7 +10072,7 @@ static vk_op_rope_push_constants ggml_vk_make_rope_constants(const ggml_tensor *
    uint32_t nb02 = src0->nb[2] / ggml_type_size(src0->type);

    vk_op_rope_push_constants rope {
-        (uint32_t)mode, (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
+        (uint32_t)mode, (uint32_t)src0->ne[0], (uint32_t)ggml_nrows(src0), (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
        freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1]}, theta_scale,
        has_ff, (uint32_t)src0->ne[2], nb01, nb02,
        { sections[0], sections[1], sections[2], sections[3] }, is_imrope, backprop, set_rows_stride,
@@ -14330,7 +14381,12 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
            }
            return true;
        case GGML_OP_UPSCALE:
-            return op->src[0]->type == GGML_TYPE_F32 && !(op->op_params[0] & GGML_SCALE_FLAG_ANTIALIAS);
+            if (op->op_params[0] & GGML_SCALE_FLAG_ANTIALIAS) {
+                if ((op->op_params[0] & 0xFF) != GGML_SCALE_MODE_BILINEAR) {
+                    return false;
+                }
+            }
+            return op->src[0]->type == GGML_TYPE_F32;
        case GGML_OP_ACC:
            return op->src[0]->type == GGML_TYPE_F32;
        case GGML_OP_CONCAT:
@@ -0,0 +1,51 @@
+#version 450
+
+#extension GL_EXT_control_flow_attributes : enable
+
+#include "types.glsl"
+
+layout (push_constant) uniform parameter
+{
+    uint32_t ne00;
+    uint32_t ne01;
+    uint32_t nb00;
+    uint32_t nb01;
+    uint32_t a_offset;
+} p;
+
+#define BLOCK_SIZE 256
+
+layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
+
+layout (binding = 0) readonly buffer A {uint data_a[];};
+layout (binding = 1) writeonly buffer D {uint data_d[];};
+
+shared uint vals[BLOCK_SIZE];
+
+void main() {
+    const uint expert_id = gl_WorkGroupID.x;
+    const uint num_elements = p.ne00 * p.ne01;
+    const uint tid = gl_LocalInvocationID.x;
+
+    uint count = 0;
+    for (uint idx = tid; idx < num_elements; idx += BLOCK_SIZE) {
+        const uint i01 = idx / p.ne00;
+        const uint i00 = idx % p.ne00;
+        const uint a = data_a[p.a_offset + i01 * p.nb01 + i00 * p.nb00];
+
+        count += uint(a == expert_id);
+    }
+
+    vals[tid] = count;
+    barrier();
+    [[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
+        if (tid < s) {
+            vals[tid] += vals[tid + s];
+        }
+        barrier();
+    }
+
+    if (tid == 0) {
+        data_d[expert_id] = vals[0];
+    }
+}
@@ -401,13 +401,7 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
    const uint sl = (data_a[a_offset + ib].scales_l[ib32/2] >> (4 * (ib32 & 1))) & 0xF;
    const uint sh = (data_a[a_offset + ib].scales_h >> (2 * ib32)) & 3;
    const uint qshift = (iqs & 16) >> 2;
-    u8vec4 qs = u8vec4(
-        data_a[a_offset + ib].qs[iq + 0],
-        data_a[a_offset + ib].qs[iq + 1],
-        data_a[a_offset + ib].qs[iq + 2],
-        data_a[a_offset + ib].qs[iq + 3]
-    );
-    qs = (qs >> qshift) & uint8_t(0xF);
+    const u8vec4 qs = unpack8((data_a_packed32[a_offset + ib].qs[iq/4] >> qshift) & 0x0F0F0F0F);

    const float dl = float(int(sl | (sh << 4)) - 32);
    return dl * vec4(
@@ -68,6 +68,7 @@ layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};

 #ifdef MUL_MAT_ID
 layout (binding = 3) readonly buffer IDS {int data_ids[];};
+layout (binding = 4) readonly buffer Counts {int data_expert_count[];};
 #endif

 layout (push_constant) uniform parameter
@@ -135,13 +136,19 @@ shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
 #include "mul_mm_funcs.glsl"

 void main() {
+    const uint ic = gl_WorkGroupID.y;
+
+#ifdef MUL_MAT_ID
+    const uint expert_idx = gl_GlobalInvocationID.z;
+    if (ic * BN >= data_expert_count[expert_idx]) {
+        return;
+    }
+#endif
 #ifdef NEEDS_INIT_IQ_SHMEM
    init_iq_shmem(gl_WorkGroupSize);
 #endif

-#ifdef MUL_MAT_ID
-    const uint expert_idx = gl_GlobalInvocationID.z;
-#else
+#ifndef MUL_MAT_ID
    const uint batch_idx = gl_GlobalInvocationID.z;

    const uint i13 = batch_idx / p.ne12;
@@ -156,7 +163,6 @@ void main() {
    const uint blocks_m = (p.M + BM - 1) / BM;
    const uint ir = gl_WorkGroupID.x % blocks_m;
    const uint ik = gl_WorkGroupID.x / blocks_m;
-    const uint ic = gl_WorkGroupID.y;

    const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
    const uint WSUBM = WM / WMITER;
@@ -92,6 +92,7 @@ layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};

 #ifdef MUL_MAT_ID
 layout (binding = 3) readonly buffer IDS {int data_ids[];};
+layout (binding = 4) readonly buffer Counts {int data_expert_count[];};

 shared u16vec4 row_ids[BN];

@@ -107,11 +108,7 @@ B_TYPE decodeFuncB(const in decodeBufB bl, const in uint blockCoords[2], const i
 {
    const uint row_i = blockCoords[0];

-    if (row_i >= _ne1) {
-        return B_TYPE(0.0);
-    }
-
-    const u16vec4 row_idx = row_ids[row_i & (BN - 1)];
+    const u16vec4 row_idx = row_ids[row_i];
    B_TYPE ret = data_b[row_idx.y * p.batch_stride_b + row_idx.x * p.stride_b + blockCoords[1]];

    return ret;
@@ -138,6 +135,8 @@ void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
    uint ids[16];
    uint iter = 0;

+    uint expert_count = data_expert_count[expert_idx];
+
    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
        // prefetch up to 16 elements
        if (iter == 0) {
@@ -185,7 +184,7 @@ void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
        }
        _ne1 += total;
        iter &= 15;
-        if (_ne1 >= (ic + 1) * BN) {
+        if (_ne1 >= (ic + 1) * BN || _ne1 == expert_count) {
            break;
        }
    }
@@ -194,15 +193,28 @@ void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
 #endif

 void main() {
+    const uint tid = gl_LocalInvocationIndex;
+    const uint ic = gl_WorkGroupID.y;
+
+#ifdef MUL_MAT_ID
+    const uint expert_idx = gl_GlobalInvocationID.z;
+    if (ic * BN >= data_expert_count[expert_idx]) {
+        return;
+    }
+    // initialize to row 0 so we don't need to bounds check
+    if (tid < BN) {
+        row_ids[tid] = u16vec4(0);
+    }
+#if !defined(NEEDS_INIT_IQ_SHMEM)
+    barrier();
+#endif
+#endif
+
 #ifdef NEEDS_INIT_IQ_SHMEM
    init_iq_shmem(gl_WorkGroupSize);
 #endif

-    const uint tid = gl_LocalInvocationIndex;
-
-#ifdef MUL_MAT_ID
-    const uint expert_idx = gl_GlobalInvocationID.z;
-#else
+#ifndef MUL_MAT_ID
    const uint batch_idx = gl_GlobalInvocationID.z;

    const uint i13 = batch_idx / p.ne12;
@@ -217,7 +229,6 @@ void main() {
    const uint blocks_m = (p.M + BM - 1) / BM;
    const uint ir = gl_WorkGroupID.x % blocks_m;
    const uint ik = gl_WorkGroupID.x / blocks_m;
-    const uint ic = gl_WorkGroupID.y;

 #ifdef MUL_MAT_ID
    if (bitCount(p.nei0) == 1) {
@@ -482,7 +493,7 @@ void main() {
                    coopmat<MAT_TYPE, gl_ScopeWorkgroup, BK, BNover4, gl_MatrixUseB> mat_b;

                    coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
-                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover4, block_k, BK), tensorViewTranspose, decodeFuncB);
+                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BNover4, block_k, BK), tensorViewTranspose, decodeFuncB);

                    sum = coopMatMulAdd(mat_a, mat_b, sum);
                } else {
@@ -490,7 +501,7 @@ void main() {
                    coopmat<MAT_TYPE, gl_ScopeWorkgroup, BK, BNover4, gl_MatrixUseB> mat_b;

                    coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutAClamp, ir * BM, BM, block_k, BK) DECODEFUNCA);
-                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover4, block_k, BK), tensorViewTranspose, decodeFuncB);
+                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BNover4, block_k, BK), tensorViewTranspose, decodeFuncB);

                    sum = coopMatMulAdd(mat_a, mat_b, sum);
                }
@@ -526,7 +537,7 @@ void main() {
                    coopmat<MAT_TYPE, gl_ScopeWorkgroup, BK, BNover2, gl_MatrixUseB> mat_b;

                    coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
-                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover2, block_k, BK), tensorViewTranspose, decodeFuncB);
+                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BNover2, block_k, BK), tensorViewTranspose, decodeFuncB);

                    sum = coopMatMulAdd(mat_a, mat_b, sum);
                } else {
@@ -534,7 +545,7 @@ void main() {
                    coopmat<MAT_TYPE, gl_ScopeWorkgroup, BK, BNover2, gl_MatrixUseB> mat_b;

                    coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutAClamp, ir * BM, BM, block_k, BK) DECODEFUNCA);
-                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BNover2, block_k, BK), tensorViewTranspose, decodeFuncB);
+                    coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BNover2, block_k, BK), tensorViewTranspose, decodeFuncB);

                    sum = coopMatMulAdd(mat_a, mat_b, sum);
                }
@@ -571,7 +582,7 @@ void main() {

                coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutA, ir * BM, BM, block_k, BK) DECODEFUNCA);
 #ifdef MUL_MAT_ID
-                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BN, block_k, BK), tensorViewTranspose, decodeFuncB);
+                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BN, block_k, BK), tensorViewTranspose, decodeFuncB);
 #else
                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutBClamp, ic * BN, BN, block_k, BK), tensorViewTranspose);
 #endif
@@ -583,7 +594,7 @@ void main() {

                coopMatLoadTensorNV(mat_a, data_a, pos_a, sliceTensorLayoutNV(tensorLayoutAClamp, ir * BM, BM, block_k, BK) DECODEFUNCA);
 #ifdef MUL_MAT_ID
-                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, ic * BN, BN, block_k, BK), tensorViewTranspose, decodeFuncB);
+                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutB, 0, BN, block_k, BK), tensorViewTranspose, decodeFuncB);
 #else
                coopMatLoadTensorNV(mat_b, data_b, pos_b, sliceTensorLayoutNV(tensorLayoutBClamp, ic * BN, BN, block_k, BK), tensorViewTranspose);
 #endif
@@ -159,14 +159,16 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
            const uint is = iqs / 8;                     // 0..15
            const uint halfsplit = ((iqs % 64) / 16);    // 0,1,2,3
            const uint qsshift = halfsplit * 2;          // 0,2,4,6
-            const uint m = 1 << (4 * n + halfsplit);     // 1,2,4,8,16,32,64,128

            const int8_t us = int8_t(((data_a[ib].scales[is % 8] >> (4 * int(is / 8))) & 0xF)
                                  | (((data_a[ib].scales[8 + (is % 4)] >> (2 * int(is / 4))) & 3) << 4));
            const float dl = float(data_a[ib].d) * float(us - 32);

-            buf_a[buf_idx] = FLOAT_TYPE_VEC2(dl * float(int8_t((data_a[ib].qs[qsi    ] >> qsshift) & 3) - (((data_a[ib].hmask[hmi    ] & m) != 0) ? 0 : 4)),
-                                             dl * float(int8_t((data_a[ib].qs[qsi + 1] >> qsshift) & 3) - (((data_a[ib].hmask[hmi + 1] & m) != 0) ? 0 : 4)));
+            const vec2 qs = vec2(unpack8((uint(data_a_packed16[ib].qs[qsi / 2]) >> qsshift) & 0x0303).xy);
+            const vec2 hm = vec2(unpack8(((uint(data_a_packed16[ib].hmask[hmi / 2]) >> (4 * n + halfsplit)) & 0x0101 ^ 0x0101) << 2).xy);
+
+            buf_a[buf_idx] = FLOAT_TYPE_VEC2(dl * (qs.x - hm.x),
+                                             dl * (qs.y - hm.y));
 #elif defined(DATA_A_Q4_K)
            const uint idx = pos_a + col * p.stride_a / LOAD_VEC_A + row;
            const uint buf_idx = col * SHMEM_STRIDE + row * LOAD_VEC_A / 2;
@@ -198,8 +200,10 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
            const float d = loadd.x * sc;
            const float m = -loadd.y * mbyte;

-            buf_a[buf_idx] = FLOAT_TYPE_VEC2(fma(d, float((data_a[ib].qs[qsi    ] >> (b * 4)) & 0xF), m),
-                                             fma(d, float((data_a[ib].qs[qsi + 1] >> (b * 4)) & 0xF), m));
+            const vec2 q = vec2(unpack8((uint(data_a_packed16[ib].qs[qsi / 2]) >> (b * 4)) & 0x0F0F).xy);
+
+            buf_a[buf_idx] = FLOAT_TYPE_VEC2(fma(d, q.x, m),
+                                             fma(d, q.y, m));
 #elif defined(DATA_A_Q5_K)
            const uint idx = pos_a + col * p.stride_a / LOAD_VEC_A + row;
            const uint buf_idx = col * SHMEM_STRIDE + row * LOAD_VEC_A / 2;
@@ -213,8 +217,6 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
            const uint qsi = n * 32 + (iqs % 16) * 2;  // 0,2,4..126
            const uint qhi = (iqs % 16) * 2;           // 0,2,4..30

-            const uint8_t hm = uint8_t(1 << (iqs / 16));
-
            const vec2 loadd = vec2(data_a[ib].dm);

            const uint scidx0 = (is < 4) ? is : (is + 4);
@@ -234,8 +236,12 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
            const float d = loadd.x * sc;
            const float m = -loadd.y * mbyte;

-            buf_a[buf_idx] = FLOAT_TYPE_VEC2(fma(d, float((data_a[ib].qs[qsi    ] >> (b * 4)) & 0xF) + float((data_a[ib].qh[qhi    ] & hm) != 0 ? 16 : 0), m),
-                                             fma(d, float((data_a[ib].qs[qsi + 1] >> (b * 4)) & 0xF) + float((data_a[ib].qh[qhi + 1] & hm) != 0 ? 16 : 0), m));
+            const uint qs = (uint(data_a_packed16[ib].qs[qsi / 2]) >> (b * 4)) & 0x0F0F;
+            const uint qh = ((uint(data_a_packed16[ib].qh[qhi / 2]) >> (iqs / 16)) & 0x0101) << 4;
+            const vec2 q = vec2(unpack8(qs | qh).xy);
+
+            buf_a[buf_idx] = FLOAT_TYPE_VEC2(fma(d, q.x, m),
+                                             fma(d, q.y, m));
 #elif defined(DATA_A_Q6_K)
            const uint idx = pos_a + col * p.stride_a / LOAD_VEC_A + row;
            const uint buf_idx = col * SHMEM_STRIDE + row * LOAD_VEC_A / 2;
@@ -394,11 +400,9 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin

            const float d = float(data_a[ib].d);
            const uint qs = data_a[ib].qs[iqs];
-            const uint signs = pack32(u8vec4(
-                data_a[ib].qs[is+0],
-                data_a[ib].qs[is+1],
-                data_a[ib].qs[is+2],
-                data_a[ib].qs[is+3]
+            const uint signs = pack32(u16vec2(
+                data_a_packed16[ib].qs[is/2],
+                data_a_packed16[ib].qs[is/2+1]
            ));
            const float db = d * 0.5 * (0.5 + (signs >> 28));
            const uint32_t sign7 = bitfieldExtract(signs, 7 * (int(iqs / 2) % 4), 7);
@@ -443,8 +447,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
            const uint sl = (data_a[ib].scales_l[ib32/2] >> (4 * (ib32 & 1))) & 0xF;
            const uint sh = ((data_a[ib].scales_h) >> (2 * ib32)) & 3;
            const uint qshift = (idx & 8) >> 1;
-            u8vec2 qs = u8vec2(data_a[ib].qs[iq], data_a[ib].qs[iq + 1]);
-            qs = (qs >> qshift) & uint8_t(0xF);
+            u8vec2 qs = unpack8((uint(data_a_packed16[ib].qs[iq/2]) >> qshift) & 0x0F0F).xy;

            const float d = float(data_a[ib].d);
            const vec2 v = d * float(int(sl | (sh << 4)) - 32) * vec2(kvalues_iq4nl[qs.x], kvalues_iq4nl[qs.y]);
@@ -13,6 +13,8 @@ void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
    uint ids[16];
    uint iter = 0;

+    uint expert_count = data_expert_count[expert_idx];
+
    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
        // prefetch up to 16 elements
        if (iter == 0) {
@@ -60,7 +62,7 @@ void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
        }
        _ne1 += total;
        iter &= 15;
-        if (_ne1 >= (ic + 1) * BN) {
+        if (_ne1 >= (ic + 1) * BN || _ne1 == expert_count) {
            break;
        }
    }
@@ -35,6 +35,7 @@ layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};

 #ifdef MUL_MAT_ID
 layout (binding = 3) readonly buffer IDS {int data_ids[];};
+layout (binding = 4) readonly buffer Counts {int data_expert_count[];};
 #endif

 layout (push_constant) uniform parameter
@@ -104,13 +105,19 @@ block_b_cache cache_b;
 #include "mul_mmq_funcs.glsl"

 void main() {
+    const uint ic = gl_WorkGroupID.y;
+
+#ifdef MUL_MAT_ID
+    const uint expert_idx = gl_GlobalInvocationID.z;
+    if (ic * BN >= data_expert_count[expert_idx]) {
+        return;
+    }
+#endif
 #ifdef NEEDS_INIT_IQ_SHMEM
    init_iq_shmem(gl_WorkGroupSize);
 #endif

-#ifdef MUL_MAT_ID
-    const uint expert_idx = gl_GlobalInvocationID.z;
-#else
+#ifndef MUL_MAT_ID
    const uint batch_idx = gl_GlobalInvocationID.z;

    const uint i13 = batch_idx / p.ne12;
@@ -125,7 +132,6 @@ void main() {
    const uint blocks_m = (p.M + BM - 1) / BM;
    const uint ir = gl_WorkGroupID.x % blocks_m;
    const uint ik = gl_WorkGroupID.x / blocks_m;
-    const uint ic = gl_WorkGroupID.y;

    const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
    const uint WSUBM = WM / WMITER;
@@ -6,6 +6,9 @@
 void main() {
    const uint i0 = 2*gl_GlobalInvocationID.y;
    // i1 is actually i2*nb2+i1, but the rows are contiguous
-    const uint i1 = gl_GlobalInvocationID.x;
+    const uint i1 = gl_GlobalInvocationID.x + 32768 * gl_GlobalInvocationID.z;
+    if (i1 >= pc.nrows) {
+        return;
+    }
    rope_multi(i0, i1, pc);
 }
@@ -6,6 +6,9 @@
 void main() {
    const uint i0 = 2*gl_GlobalInvocationID.y;
    // i1 is actually i2*nb2+i1, but the rows are contiguous
-    const uint i1 = gl_GlobalInvocationID.x;
+    const uint i1 = gl_GlobalInvocationID.x + 32768 * gl_GlobalInvocationID.z;
+    if (i1 >= pc.nrows) {
+        return;
+    }
    rope_neox(i0, i1, pc);
 }
@@ -6,6 +6,9 @@
 void main() {
    const uint i0 = 2*gl_GlobalInvocationID.y;
    // i1 is actually i2*nb2+i1, but the rows are contiguous
-    const uint i1 = gl_GlobalInvocationID.x;
+    const uint i1 = gl_GlobalInvocationID.x + 32768 * gl_GlobalInvocationID.z;
+    if (i1 >= pc.nrows) {
+        return;
+    }
    rope_norm(i0, i1, pc);
 }
@@ -6,6 +6,7 @@
 struct rope_params {
    uint rope_mode;
    uint ncols;
+    uint nrows;
    uint n_dims;
    float freq_scale;
    uint p_delta_rows;
@@ -6,6 +6,9 @@
 void main() {
    const uint i0 = 2*gl_GlobalInvocationID.y;
    // i1 is actually i2*nb2+i1, but the rows are contiguous
-    const uint i1 = gl_GlobalInvocationID.x;
+    const uint i1 = gl_GlobalInvocationID.x + 32768 * gl_GlobalInvocationID.z;
+    if (i1 >= pc.nrows) {
+        return;
+    }
    rope_vision(i0, i1, pc);
 }
@@ -172,16 +172,12 @@ struct block_q8_0
    float16_t d;
    int8_t qs[32];
 };
+
 struct block_q8_0_packed16
 {
    float16_t d;
    int16_t qs[32/2];
 };
-struct block_q8_0_packed32
-{
-    float16_t d;
-    int32_t qs[32/4];
-};

 #if defined(DATA_A_Q8_0)
 #define QUANT_K QUANT_K_Q8_0
@@ -189,7 +185,6 @@ struct block_q8_0_packed32
 #define QUANT_AUXF 1
 #define A_TYPE block_q8_0
 #define A_TYPE_PACKED16 block_q8_0_packed16
-#define A_TYPE_PACKED32 block_q8_0_packed32
 #define DATA_A_QUANT_LEGACY
 #endif

@@ -201,11 +196,13 @@ struct block_q8_1
    f16vec2 ds;
    int8_t qs[32];
 };
+
 struct block_q8_1_packed16
 {
    f16vec2 ds;
    int16_t qs[16];
 };
+
 struct block_q8_1_packed32
 {
    f16vec2 ds;
@@ -218,6 +215,7 @@ struct block_q8_1_x4
    f16vec2 ds[4];
    int32_t qs[32];
 };
+
 struct block_q8_1_x4_packed128
 {
    f16vec2 ds[4];
@@ -1346,10 +1344,28 @@ struct block_iq4_xs
    uint8_t qs[QUANT_K_IQ4_XS/2];
 };

+struct block_iq4_xs_packed16
+{
+    float16_t d;
+    uint16_t scales_h;
+    uint16_t scales_l[QUANT_K_IQ4_XS/128];
+    uint16_t qs[QUANT_K_IQ4_XS/4];
+};
+
+struct block_iq4_xs_packed32
+{
+    float16_t d;
+    uint16_t scales_h;
+    uint32_t scales_l;
+    uint32_t qs[QUANT_K_IQ4_XS/8];
+};
+
 #if defined(DATA_A_IQ4_XS)
 #define QUANT_K QUANT_K_IQ4_XS
 #define QUANT_R QUANT_R_IQ4_XS
 #define A_TYPE block_iq4_xs
+#define A_TYPE_PACKED16 block_iq4_xs_packed16
+#define A_TYPE_PACKED32 block_iq4_xs_packed32
 #endif

 #define QUANT_K_IQ4_NL 32
@@ -21,6 +21,7 @@ layout (binding = 1) writeonly buffer D {D_TYPE data_d[];};
 #define NEAREST  0
 #define BILINEAR 1
 #define BICUBIC  2
+#define BILINEAR_ANTIALIAS 513

 layout (constant_id = 0) const uint scale_mode = 0;

@@ -62,6 +63,56 @@ float interpolate_bilinear(uint i10, uint i11, uint i12, uint i13) {
    return fetch_bilinear(c0, c1, d, i12, i13);
 }

+float triangle_filter(float x) {
+    return max(1.0f - abs(x), 0.0f);
+}
+
+float interpolate_bilinear_antialias(uint i10, uint i11, uint i12, uint i13) {
+    const float support1  = max(1.0f, 1.0f / p.sf1);
+    const float invscale1 = 1.0f / support1;
+    const float support0  = max(1.0f, 1.0f / p.sf0);
+    const float invscale0 = 1.0f / support0;
+
+    const uint i02 = uint(i12 / p.sf2);
+    const uint i03 = uint(i13 / p.sf3);
+
+    const float y = (float(i11) + p.pixel_offset) / p.sf1;
+    const float x = (float(i10) + p.pixel_offset) / p.sf0;
+
+    // the range of source pixels that contribute
+    const int x_min = max(int(x - support0 + p.pixel_offset), 0);
+    const int x_max = min(int(x + support0 + p.pixel_offset), int(p.ne00));
+    const int y_min = max(int(y - support1 + p.pixel_offset), 0);
+    const int y_max = min(int(y + support1 + p.pixel_offset), int(p.ne01));
+
+    // bilinear filter with antialiasing
+    float val = 0.0f;
+    float total_weight = 0.0f;
+
+    for (int sy = y_min; sy < y_max; sy++) {
+        const float weight_y = triangle_filter((sy - y + p.pixel_offset) * invscale1);
+
+        for (int sx = x_min; sx < x_max; sx++) {
+            const float weight_x = triangle_filter((sx - x + p.pixel_offset) * invscale0);
+            const float weight = weight_x * weight_y;
+
+            if (weight <= 0.0f) {
+                continue;
+            }
+
+            const float pixel = data_a[p.a_offset + i03 * p.nb03 + i02 * p.nb02 + sy * p.nb01 + sx * p.nb00];
+            val += pixel * weight;
+            total_weight += weight;
+        }
+    }
+
+    if (total_weight > 0.0f) {
+        val /= total_weight;
+    }
+
+    return val;
+}
+
 // Bicubic interpolation with alpha = -0.75
 // https://en.wikipedia.org/wiki/Bicubic_interpolation#Bicubic_convolution_algorithm
 const vec4 bcoeffs1 = vec4( 1.25, -2.25,  0.0, 1.0);
@@ -118,6 +169,9 @@ void main() {
        case BICUBIC:
            result = interpolate_bicubic(i10, i11, i12, i13);
            break;
+        case BILINEAR_ANTIALIAS:
+            result = interpolate_bilinear_antialias(i10, i11, i12, i13);
+            break;
    }

    data_d[p.d_offset + idx] = D_TYPE(result);
@@ -945,6 +945,8 @@ void process_shaders() {
    string_to_spv("count_equal_i32", "count_equal.comp", merge_maps(base_dict, {{"A_TYPE", "int"}, {"B_TYPE", "int"}, {"D_TYPE", "int"}}));
    string_to_spv("cumsum_f32", "cumsum.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));

+    string_to_spv("count_experts", "count_experts.comp", merge_maps(base_dict, {{"A_TYPE", "uint"}, {"D_TYPE", "uint"}}));
+
    for (std::string dim_str : {"", "_3d"}) {
        for (bool bda : {false, true}) {
            std::string bda_str = bda ? "_bda" : "";
@@ -286,7 +286,7 @@ extern "C" {
        // NULL-terminated list of buffer types to use for tensors that match a pattern
        const struct llama_model_tensor_buft_override * tensor_buft_overrides;

-        int32_t n_gpu_layers; // number of layers to store in VRAM
+        int32_t n_gpu_layers; // number of layers to store in VRAM, a negative value means all layers
        enum llama_split_mode split_mode; // how to split the model across multiple GPUs

        // the GPU that is used for the entire model when split_mode is LLAMA_SPLIT_MODE_NONE
@@ -467,10 +467,17 @@ extern "C" {
    // Frees all allocated memory
    LLAMA_API void llama_free(struct llama_context * ctx);

+    enum llama_params_fit_status {
+        LLAMA_PARAMS_FIT_STATUS_SUCCESS = 0, // found allocations that are projected to fit
+        LLAMA_PARAMS_FIT_STATUS_FAILURE = 1, // could not find allocations that are projected to fit
+        LLAMA_PARAMS_FIT_STATUS_ERROR   = 2, // a hard error occured, e.g. because no model could be found at the specified path
+    };
+
    // fits mparams and cparams to free device memory (assumes system memory is unlimited)
-    // returns true if the parameters could be successfully modified to fit device memory
-    // this function is NOT thread safe because it modifies the global llama logger state
-    LLAMA_API bool llama_params_fit(
+    //   - returns true if the parameters could be successfully modified to fit device memory
+    //   - this function is NOT thread safe because it modifies the global llama logger state
+    //   - only parameters that have the same value as in llama_default_model_params are modified
+    LLAMA_API enum llama_params_fit_status llama_params_fit(
                                   const char   * path_model,
                    struct llama_model_params   * mparams,
                    struct llama_context_params * cparams,
@@ -294,8 +294,8 @@ llama_context::llama_context(
        // enabling pipeline parallelism in the scheduler increases memory usage, so it is only done when necessary
        bool pipeline_parallel =
            model.n_devices() > 1 &&
-            model.params.n_gpu_layers > (int) model.hparams.n_layer &&
-            model.params.split_mode == LLAMA_SPLIT_MODE_LAYER &&
+            model.n_gpu_layers() > model.hparams.n_layer &&
+            model.split_mode() == LLAMA_SPLIT_MODE_LAYER &&
            cparams.offload_kqv &&
            !model.has_tensor_overrides();

@@ -1570,7 +1570,7 @@ llm_graph_cb llama_context::graph_get_cb() const {

        // norm may be automatically assigned to the backend of the previous layer, increasing data transfer between backends
        // FIXME: fix in ggml_backend_sched
-        const bool full_offload = model.params.n_gpu_layers > (int) model.hparams.n_layer;
+        const bool full_offload = model.n_gpu_layers() > model.hparams.n_layer;
        if (ubatch.n_tokens < 32 || full_offload) {
            if (il != -1 && strcmp(name, "norm") == 0) {
                const auto & dev_layer = model.dev_layer(il);
@@ -2378,11 +2378,11 @@ void llama_model::load_vocab(llama_model_loader & ml) {

 bool llama_model::load_tensors(llama_model_loader & ml) {
    const auto & split_mode   = params.split_mode;
-    const auto & n_gpu_layers = params.n_gpu_layers;
    const auto & use_mlock    = params.use_mlock;
    const auto & tensor_split = params.tensor_split;

-    const int n_layer = hparams.n_layer;
+    const int n_layer      = hparams.n_layer;
+    const int n_gpu_layers = this->n_gpu_layers();

    const bool use_mmap_buffer = true;

@@ -6884,6 +6884,14 @@ size_t llama_model::n_devices() const {
    return devices.size();
 }

+uint32_t llama_model::n_gpu_layers() const {
+    return params.n_gpu_layers >= 0 ? params.n_gpu_layers : hparams.n_layer + 1;
+}
+
+llama_split_mode llama_model::split_mode() const {
+    return params.split_mode;
+}
+
 std::map<ggml_backend_buffer_type_t, size_t> llama_model::memory_breakdown() const {
    std::map<ggml_backend_buffer_type_t, size_t> ret;
    for (const auto & [ctx, bufs] : pimpl->ctxs_bufs) {
@@ -7794,7 +7802,7 @@ llama_model_params llama_model_default_params() {
    llama_model_params result = {
        /*.devices                     =*/ nullptr,
        /*.tensor_buft_overrides       =*/ nullptr,
-        /*.n_gpu_layers                =*/ 999,
+        /*.n_gpu_layers                =*/ -1,
        /*.split_mode                  =*/ LLAMA_SPLIT_MODE_LAYER,
        /*.main_gpu                    =*/ 0,
        /*.tensor_split                =*/ nullptr,
@@ -466,8 +466,6 @@ struct llama_model {
    struct ggml_tensor * dense_2_out_layers = nullptr;
    struct ggml_tensor * dense_3_out_layers = nullptr;

-    llama_model_params params;
-
    // gguf metadata
    std::unordered_map<std::string, std::string> gguf_kv;

@@ -498,6 +496,9 @@ struct llama_model {
    size_t n_tensors() const;
    size_t n_devices() const;

+    uint32_t n_gpu_layers() const;
+    llama_split_mode split_mode() const;
+
    std::map<ggml_backend_buffer_type_t, size_t> memory_breakdown() const;

    // total number of parameters in the model
@@ -526,6 +527,8 @@ struct llama_model {
    ggml_cgraph * build_graph(const llm_graph_params & params) const;

 private:
+    llama_model_params params;
+
    struct impl;
    std::unique_ptr<impl> pimpl;
 };
@@ -140,6 +140,10 @@ enum layer_fraction_t {
 };
 // this enum is only used in llama_params_fit_impl but needs to be defined outside of it to fix a Windows compilation issue

+class llama_params_fit_exception : public std::runtime_error {
+    using std::runtime_error::runtime_error;
+};
+
 static void llama_params_fit_impl(
        const char * path_model, struct llama_model_params * mparams, struct llama_context_params * cparams,
        float * tensor_split, struct llama_model_tensor_buft_override * tensor_buft_overrides,
@@ -181,12 +185,11 @@ static void llama_params_fit_impl(
        }
    }

-    int64_t sum_total           = 0;
+    int64_t sum_free            = 0;
    int64_t sum_projected_free  = 0;
    int64_t min_projected_free  = INT64_MAX;
    int64_t sum_projected_used  = 0;
    int64_t sum_projected_model = 0;
-    int64_t sum_projected_ctx   = 0;

    if (nd > 1) {
        LLAMA_LOG_INFO("%s: projected memory use with initial parameters [MiB]:\n", __func__);
@@ -197,12 +200,11 @@ static void llama_params_fit_impl(
        const int64_t projected_used = dmd.mb.total();
        const int64_t projected_free = dmd.free - projected_used;

-        sum_total           += dmd.total;
+        sum_free            += dmd.free;
        sum_projected_used  += projected_used;
        sum_projected_free  += projected_free;
        min_projected_free   = std::min(min_projected_free, projected_free);
        sum_projected_model += dmd.mb.model;
-        sum_projected_ctx   += dmd.mb.context;

        if (nd > 1) {
            LLAMA_LOG_INFO("%s:   - %s: %6" PRId64 " total, %6" PRId64 " used, %6" PRId64 " %s\n",
@@ -210,10 +212,9 @@ static void llama_params_fit_impl(
                projected_free >= 0 ? "surplus" : "deficit");
        }
    }
-    assert(sum_total >= 0 && sum_projected_used >= 0 && sum_projected_ctx >= 0);
-    assert(sum_projected_used >= sum_projected_ctx);
+    assert(sum_free >= 0 && sum_projected_used >= 0);
    LLAMA_LOG_INFO("%s: projected to use %" PRId64 " MiB of device memory vs. %" PRId64 " MiB of free device memory\n",
-        __func__, sum_projected_used/MiB, sum_total/MiB);
+        __func__, sum_projected_used/MiB, sum_free/MiB);
    if (min_projected_free >= margin) {
        if (nd == 1) {
            LLAMA_LOG_INFO("%s: will leave %" PRId64 " >= %" PRId64 " MiB of free device memory, no changes needed\n",
@@ -236,9 +237,7 @@ static void llama_params_fit_impl(
                __func__, margin/MiB, -global_surplus/MiB);
            if (cparams->n_ctx == 0) {
                if (hp_nct > n_ctx_min) {
-                    const int64_t bytes_per_ctx = sum_projected_ctx / hp_nct;
-
-                    int64_t memory_reduction = -global_surplus;
+                    int64_t sum_used_target = sum_free - nd*margin_s;
                    if (nd > 1) {
                        // for multiple devices we need to be more conservative in terms of how much context we think can fit:
                        //   - for dense models only whole layers can be assigned to devices
@@ -246,24 +245,34 @@ static void llama_params_fit_impl(
                        //   - on average we expect a waste of 0.5 layers/tensors per device
                        //   - use slightly more than the expected average for nd devices to be safe
                        const int64_t model_per_layer = sum_projected_model / std::min(uint32_t(mparams->n_gpu_layers), hp_ngl);
-                        memory_reduction += (nd + 1) * model_per_layer / (hp_nex == 0 ? 2 : 6);
+                        sum_used_target -= (nd + 1) * model_per_layer / (hp_nex == 0 ? 2 : 6);
                    }

-                    uint32_t ctx_reduction = std::min(uint32_t((memory_reduction + bytes_per_ctx - 1) / bytes_per_ctx), hp_nct - n_ctx_min);
-                    cparams->n_ctx = hp_nct - ctx_reduction;
-                    cparams->n_ctx = std::max(cparams->n_ctx - cparams->n_ctx % 256, n_ctx_min); // round down context for CUDA backend
+                    int64_t sum_projected_used_min_ctx = 0;
+                    cparams->n_ctx = n_ctx_min;
+                    const dmds_t dmds_min_ctx = llama_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
+                    for (const auto & dmd : dmds_min_ctx) {
+                        sum_projected_used_min_ctx += dmd.mb.total();
+                    }
+                    if (sum_used_target > sum_projected_used_min_ctx) {
+                        // linear interpolation between minimum and maximum context size:
+                        cparams->n_ctx += (hp_nct - n_ctx_min) * (sum_used_target - sum_projected_used_min_ctx)
+                            / (sum_projected_used - sum_projected_used_min_ctx);
+                        cparams->n_ctx = std::max(cparams->n_ctx - cparams->n_ctx % 256, n_ctx_min); // round down context for CUDA backend

-                    ctx_reduction = hp_nct - cparams->n_ctx;
-                    memory_reduction = ctx_reduction * bytes_per_ctx;
-                    global_surplus += memory_reduction;
-                    LLAMA_LOG_INFO("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
-                        __func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
-                    if (global_surplus >= 0) {
+                        const int64_t bytes_per_ctx = (sum_projected_used - sum_projected_used_min_ctx) / (hp_nct - n_ctx_min);
+                        const int64_t memory_reduction = (hp_nct - cparams->n_ctx) * bytes_per_ctx;
+                        LLAMA_LOG_INFO("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
+                            __func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
                        if (nd == 1) {
                            LLAMA_LOG_INFO("%s: entire model can be fit by reducing context\n", __func__);
                            return;
                        }
                        LLAMA_LOG_INFO("%s: entire model should be fit across devices by reducing context\n", __func__);
+                    } else {
+                        const int64_t memory_reduction = sum_projected_used - sum_projected_used_min_ctx;
+                        LLAMA_LOG_INFO("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
+                            __func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
                    }
                } else {
                    LLAMA_LOG_INFO("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
@@ -276,28 +285,28 @@ static void llama_params_fit_impl(
    }

    if (mparams->n_gpu_layers != default_mparams.n_gpu_layers) {
-        throw std::runtime_error("n_gpu_layers already set by user to " + std::to_string(mparams->n_gpu_layers) + ", abort");
+        throw llama_params_fit_exception("n_gpu_layers already set by user to " + std::to_string(mparams->n_gpu_layers) + ", abort");
    }
    if (nd > 1) {
        if (!tensor_split) {
-            throw std::runtime_error("did not provide a buffer to write the tensor_split to, abort");
+            throw llama_params_fit_exception("did not provide a buffer to write the tensor_split to, abort");
        }
        if (mparams->tensor_split) {
            for (size_t id = 0; id < nd; id++) {
                if (mparams->tensor_split[id] != 0.0f) {
-                    throw std::runtime_error("model_params::tensor_split already set by user, abort");
+                    throw llama_params_fit_exception("model_params::tensor_split already set by user, abort");
                }
            }
        }
        if (mparams->split_mode == LLAMA_SPLIT_MODE_ROW) {
-            throw std::runtime_error("changing weight allocation for LLAMA_SPLIT_MODE_ROW not implemented, abort");
+            throw llama_params_fit_exception("changing weight allocation for LLAMA_SPLIT_MODE_ROW not implemented, abort");
        }
    }
    if (!tensor_buft_overrides) {
-        throw std::runtime_error("did not provide buffer to set tensor_buft_overrides, abort");
+        throw llama_params_fit_exception("did not provide buffer to set tensor_buft_overrides, abort");
    }
    if (mparams->tensor_buft_overrides && (mparams->tensor_buft_overrides->pattern || mparams->tensor_buft_overrides->buft)) {
-        throw std::runtime_error("model_params::tensor_buft_overrides already set by user, abort");
+        throw llama_params_fit_exception("model_params::tensor_buft_overrides already set by user, abort");
    }

    // step 3: iteratively fill the back to front with "dense" layers
@@ -380,7 +389,7 @@ static void llama_params_fit_impl(
                    tensor_buft_overrides[itbo].buft    = nullptr;
                    itbo++;
                    mparams.tensor_buft_overrides = tensor_buft_overrides;
-                    throw std::runtime_error("llama_params_fit_n_tensor_buft_overrides() == "
+                    throw llama_params_fit_exception("llama_params_fit_n_tensor_buft_overrides() == "
                        + std::to_string(ntbo) + " is insufficient for model\n");
                }
                tensor_buft_overrides[itbo].pattern = get_overflow_pattern(il, il == il0 ? ngl_per_device[id].overflow_type : LAYER_FRACTION_MOE);
@@ -678,22 +687,25 @@ static void llama_params_fit_impl(
    set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, *mparams);
 }

-bool llama_params_fit(
+enum llama_params_fit_status llama_params_fit(
        const char * path_model, struct llama_model_params * mparams, struct llama_context_params * cparams,
        float * tensor_split, struct llama_model_tensor_buft_override * tensor_buft_overrides,
        size_t margin_s, uint32_t n_ctx_min, enum ggml_log_level log_level) {
    const int64_t t0_us = llama_time_us();
-    bool ok = true;
+    llama_params_fit_status status = LLAMA_PARAMS_FIT_STATUS_SUCCESS;
    try {
        llama_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margin_s, n_ctx_min, log_level);
        LLAMA_LOG_INFO("%s: successfully fit params to free device memory\n", __func__);
-    } catch (const std::runtime_error & e) {
+    } catch (const llama_params_fit_exception & e) {
        LLAMA_LOG_WARN("%s: failed to fit params to free device memory: %s\n", __func__, e.what());
-        ok = false;
+        status = LLAMA_PARAMS_FIT_STATUS_FAILURE;
+    } catch (const std::runtime_error & e) {
+        LLAMA_LOG_ERROR("%s: encountered an error while trying to fit params to free device memory: %s\n", __func__, e.what());
+        status = LLAMA_PARAMS_FIT_STATUS_ERROR;
    }
    const int64_t t1_us = llama_time_us();
    LLAMA_LOG_INFO("%s: fitting params to free memory took %.2f seconds\n", __func__, (t1_us - t0_us) * 1e-6);
-    return ok;
+    return status;
 }

 struct llama_sampler_chain_params llama_sampler_chain_default_params() {
@@ -402,12 +402,20 @@ static std::string var_to_str(ggml_op_pool pool) {
 }

 static std::string var_to_str(ggml_scale_mode mode) {
-    switch (mode) {
-        case GGML_SCALE_MODE_NEAREST:  return "nearest";
-        case GGML_SCALE_MODE_BILINEAR: return "bilinear";
-        case GGML_SCALE_MODE_BICUBIC:  return "bicubic";
-        default:                       return std::to_string(mode);
+    std::string str;
+    switch (mode & 0xFF) {
+        case GGML_SCALE_MODE_NEAREST:  str = "nearest"; break;
+        case GGML_SCALE_MODE_BILINEAR: str = "bilinear"; break;
+        case GGML_SCALE_MODE_BICUBIC:  str = "bicubic"; break;
+        default:                       str = std::to_string(mode); break;
    }
+    if (mode & GGML_SCALE_FLAG_ALIGN_CORNERS) {
+        str += "|align_corners";
+    }
+    if (mode & GGML_SCALE_FLAG_ANTIALIAS) {
+        str += "|antialias";
+    }
+    return str;
 }

 #define VAR_TO_STR(x) (#x "=" + var_to_str(x))
@@ -5535,18 +5543,16 @@ struct test_interpolate : public test_case {
    const ggml_type type;
    const std::array<int64_t, 4> ne;
    const std::array<int64_t, 4> ne_tgt;
-    const uint32_t mode = GGML_SCALE_MODE_NEAREST;
+    const ggml_scale_mode mode = GGML_SCALE_MODE_NEAREST;

    std::string vars() override {
-        ggml_scale_mode mode = (ggml_scale_mode)(this->mode & 0xFF);
-        std::string flags = (this->mode & GGML_SCALE_FLAG_ALIGN_CORNERS) ? "align_corners" : "none";
-        return VARS_TO_STR5(type, ne, ne_tgt, mode, flags);
+        return VARS_TO_STR4(type, ne, ne_tgt, mode);
    }

    test_interpolate(ggml_type type = GGML_TYPE_F32,
            std::array<int64_t, 4> ne     = {2, 5,  7, 11},
            std::array<int64_t, 4> ne_tgt = {5, 7, 11, 13},
-            uint32_t mode = GGML_SCALE_MODE_NEAREST)
+            ggml_scale_mode mode = GGML_SCALE_MODE_NEAREST)
        : type(type), ne(ne), ne_tgt(ne_tgt), mode(mode) {}

    ggml_tensor * build_graph(ggml_context * ctx) override {
@@ -7775,6 +7781,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
                                    test_cases.emplace_back(new test_rope(type, {128,  40, 2, 1}, 128, GGML_ROPE_TYPE_NORMAL, 512, fs, ef, af, ff, v, fw)); // llama 13B
                                    test_cases.emplace_back(new test_rope(type, {128,  52, 2, 1}, 128, GGML_ROPE_TYPE_NORMAL, 512, fs, ef, af, ff, v, fw)); // llama 30B
                                    test_cases.emplace_back(new test_rope(type, {128,  64, 2, 1}, 128, GGML_ROPE_TYPE_NORMAL, 512, fs, ef, af, ff, v, fw)); // llama 65B
+                                    test_cases.emplace_back(new test_rope(type, {16, 16, 8192, 1}, 16, GGML_ROPE_TYPE_NORMAL, 512, fs, ef, af, ff, v, fw));
                                }

                                if (all) {
@@ -7789,6 +7796,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
                                    test_cases.emplace_back(new test_rope(type, { 80,  32, 2, 1},  20, GGML_ROPE_TYPE_NEOX, 512, fs, ef, af, ff, v, fw)); // neox (stablelm)
                                    test_cases.emplace_back(new test_rope(type, { 80,  32, 2, 1},  32, GGML_ROPE_TYPE_NEOX, 512, fs, ef, af, ff, v, fw)); // neox (phi-2)
                                    test_cases.emplace_back(new test_rope(type, { 80,  32, 4, 1},  32, GGML_ROPE_TYPE_NEOX, 512, fs, ef, af, ff, v, fw)); // neox (phi-2)
+                                    test_cases.emplace_back(new test_rope(type, { 16, 16, 8192, 1},  16, GGML_ROPE_TYPE_NEOX, 512, fs, ef, af, ff, v, fw));
                                }

                                if (all) {
@@ -7802,6 +7810,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
                                    test_cases.emplace_back(new test_rope(type, {128,  28, 2, 1},  32, GGML_ROPE_TYPE_IMROPE,  512, fs, ef, af, ff, v, fw));
                                    test_cases.emplace_back(new test_rope(type, { 80,  16, 2, 1},  80, GGML_ROPE_TYPE_VISION, 512, fs, ef, af, ff, v, fw)); // rope_multi,m-rope (qwen2vl ViT)
                                    test_cases.emplace_back(new test_rope(type, {128,  16, 2, 1}, 128, GGML_ROPE_TYPE_IMROPE, 512, fs, ef, af, ff, v, fw)); // rope_multi,m-rope (qwen3vl)
+                                    test_cases.emplace_back(new test_rope(type, {16, 16, 8192, 1}, 16, GGML_ROPE_TYPE_IMROPE, 512, fs, ef, af, ff, v, fw));
                                }

                                test_cases.emplace_back(new test_rope(type, { 64, 128, 2, 1},  64, GGML_ROPE_TYPE_NEOX, 512, fs, ef, af, ff, v, fw)); // neox (falcon 40B)
@@ -7880,9 +7889,9 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {5, 7, 11, 13}, {2, 5,  7, 11}, mode));
    }
    for (ggml_scale_mode mode : {GGML_SCALE_MODE_BILINEAR, GGML_SCALE_MODE_BICUBIC}) {
-        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {2, 5, 7, 11}, {5, 7, 11, 13}, mode | GGML_SCALE_FLAG_ALIGN_CORNERS));
-        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {1, 4, 3, 2}, {2, 8, 3, 2}, mode | GGML_SCALE_FLAG_ALIGN_CORNERS));
-        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {4, 1, 3, 2}, {1, 1, 3, 2}, mode | GGML_SCALE_FLAG_ALIGN_CORNERS));
+        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {2, 5, 7, 11}, {5, 7, 11, 13}, (ggml_scale_mode)(mode | GGML_SCALE_FLAG_ALIGN_CORNERS)));
+        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {1, 4, 3, 2}, {2, 8, 3, 2}, (ggml_scale_mode)(mode | GGML_SCALE_FLAG_ALIGN_CORNERS)));
+        test_cases.emplace_back(new test_interpolate(GGML_TYPE_F32, {4, 1, 3, 2}, {1, 1, 3, 2}, (ggml_scale_mode)(mode | GGML_SCALE_FLAG_ALIGN_CORNERS)));
    }

    test_cases.emplace_back(new test_sum());
@@ -26,10 +26,10 @@ int main(int argc, char ** argv) {
    llama_numa_init(params.numa);
    auto mparams = common_model_params_to_llama(params);
    auto cparams = common_context_params_to_llama(params);
-    const bool success = llama_params_fit(params.model.path.c_str(), &mparams, &cparams,
+    const llama_params_fit_status status = llama_params_fit(params.model.path.c_str(), &mparams, &cparams,
        params.tensor_split, params.tensor_buft_overrides.data(), params.fit_params_target, params.fit_params_min_ctx,
        params.verbosity >= 4 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
-    if (!success) {
+    if (status != LLAMA_PARAMS_FIT_STATUS_SUCCESS) {
        LOG_ERR("%s: failed to fit CLI arguments to free memory, exiting...\n", __func__);
        exit(1);
    }
@@ -1007,8 +1007,10 @@ private:
        return ret;
    }

-    void clear_slot(server_slot & slot) const {
-        GGML_ASSERT(!slot.is_processing());
+    void clear_slot(server_slot & slot, bool allow_processing = false) const {
+        if (!allow_processing) {
+            GGML_ASSERT(!slot.is_processing());
+        }

        SLT_WRN(slot, "clearing slot with %zu tokens\n", slot.prompt.tokens.size());

@@ -2336,7 +2338,7 @@ private:
                    if (!llama_memory_seq_rm(llama_get_memory(ctx), slot.id, p0, -1)) {
                        SLT_WRN(slot, "failed to truncate tokens with position >= %d - clearing the memory\n", p0);

-                        clear_slot(slot);
+                        clear_slot(slot, /*allow_processing=*/true);

                        // there is no common part left
                        slot.n_prompt_tokens_cache = 0;
Author	SHA1	Message	Date
Johannes Gäßler	026d2ad472	llama: fix magic number of 999 for GPU layers (#18266 ) * llama: fix magic number of 999 for GPU layers * use strings for -ngl, -ngld * enacapsulate n_gpu_layers, split_mode	2025-12-27 20:18:35 +01:00
Aman Gupta	06705fdcb3	ggml-cuda: Use same regex for GGML_NATIVE=OFF (#18407 )	2025-12-27 19:56:27 +08:00
Johannes Gäßler	a52dc60ba3	llama_fit_params: return enum for fail vs. error (#18374 )	2025-12-27 09:59:19 +01:00
Johannes Gäßler	9045c9afe5	llama-fit-params: fix Gemma 3 calculation (#18372 )	2025-12-27 09:56:04 +01:00
Jeff Bolz	c9ced4910b	vulkan: preprocess mul_mat_id experts and discard workgroups more quickly (#18352 ) Run a preprocess to count how many times each expert is used, and use this to quickly discard workgroups that aren't needed.	2025-12-26 16:12:58 -06:00
Jeff Bolz	7ac8902133	vulkan: optimize decodeFuncB in coopmat2 mul_mat_id shader (#18349 ) * vulkan: Use BK=32 for coopmat2 mul_mat_id * vulkan: optimize decodeFuncB in coopmat2 mul_mat_id shader Disable robustness, remove the OOB check in decodeFuncB, and initialize the row_ids to zero to avoid OOB access. Don't slice/offset the B matrix to ic * BN, only to adjust the coord back down to the range [0, BN) in decodeFuncB. Instead just slice with a row offset of zero and remove the '& (BN - 1)'. This allows the compiler to common some of the shared memory loads.	2025-12-26 18:15:50 +01:00
Jeff Bolz	9bf20d8ac3	vulkan: Use BK=32 for coopmat2 mul_mat_id (#18332 )	2025-12-26 18:15:02 +01:00
Eve	cb999704fb	vulkan: small dequantization improvements (#18380 ) * iq4_xs * quants	2025-12-26 18:12:11 +01:00
Jeff Bolz	b96b82fc85	vulkan: Support UPSCALE w/antialias (#18327 )	2025-12-26 17:00:57 +01:00
Jeff Bolz	10dc500bdb	vulkan: handle rope with large number of rows (#18306 )	2025-12-26 16:53:46 +01:00
o7si	4893cc07bb	server : fix crash when seq_rm fails for hybrid/recurrent models (#18391 ) * server : fix crash when seq_rm fails for hybrid/recurrent models * server : add allow_processing param to clear_slot	2025-12-26 16:35:29 +01:00