All entries

vulkan: Convert FILL to distribute workgroups in 2D to avoid exceeding maxComputeWorkGroupCount (#28592) divide workload to 2D This is to workaround FILL exceeding maxComputeWorkGroupCount for Intel G

vulkan: use spec constant for matrix matrix multiplication A-type (#25773) vulkan: use spec constant for mul mat type_a vulkan: use map for mul_mm shapes cleanup fix indentation fix cm2 and shmem init

Use Ollama models in ChatGPT Desktop Ollama models can now be used directly in ChatGPT Desktop, so you can keep your existing workflow while running open models. Setup is available from the Ollama app

hexagon: add RELU and LEAKY_RELU ops (#28585) hexagon: add RELU op hexagon: add LEAKY_RELU op too Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45844223 m

model : support Kimi-K3 recurrent-state rollback (#28466) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45866131 macOS/iOS: macOS Apple Silicon (arm64) ma

opencl: properly handle non-contiguous inputs to conv2d (#28503) opencl: fix conv2d non-contiguous strides opencl: format Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp

chat : split specialized parsers into common/parsers (#27764) chat : split specialized parsers into common/parsers Move the 14 dedicated template parsers out of chat.cpp into one file each under commo

Fix Vulkan-Hpp handle usage on 32-bit targets. (#22892) On 32-bit platforms, Vulkan non-dispatchable handles such as VkBuffer are represented as uint64_t, and Vulkan-Hpp disables implicit conversions

vulkan : fuse UNARY(GELU|SIGMOID|SILU|SOFTPLUS) + MUL (#27220) vulkan : fuse UNARY(SIGMOID|SILU|SOFTPLUS) + MUL vulkan : fuse UNARY(SIGMOID|SILU|SOFTPLUS) + MUL implement fusion in unary.comp behind U

llama : add missing headers (#28566) fix compile-error: add missing header Bug: #28557 Signed-off-by: Pepper Gray hello@peppergray.xyz fix compile-error: add missing header Bug: #28559 Signed-off-by:

metal : fix idle threads in mul_mv_iq3_xxs for ne00 < 1024 (#28086) metal : fix half-idle simdgroup in kernel_mul_mv_iq3_xxs_f32 for ne00 < 1024 metal : keep N_R0_IQ3_XXS = 4, dispatch a separate 8-ro

server : apply checkpoint min-step eviction only when the checkpoint list is full (#28302) The spacing eviction in create_checkpoint() keeps the oldest checkpoint and erases every later one within che

Revert 'ggml-cuda : restore prop.integrated on HIP builds (#24233)' (#28604) This reverts commit c7d8722. Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/46

llama: disable lazy tensor loading by default on iGPUs (#28326) llama: add lazy mode auto, fix iGPU regression revert changes except disabling lazy load on iGPUs in AUTO Website: https://llama.app Att

vulkan: add TQ1_0 support (mm, mat-vec, mat-vec-id, dequant, get_rows) (#27765) vulkan: add TQ1_0 support (mm, mat-vec, dequant, get_rows) vulkan: pack TQ1_0 powers of 3 into a 32-bit constant Replace

vulkan: rms_norm fusion opportunities (#28024) Support RMS_NORM + MUL + ADD (+ MUL) and RMS_NORM + VIEW + SET_ROWS. Extend ROPE + VIEW + SET_ROWS to support IMROPE. Worth around 4% in gemma4 on my sys

ggml: allow backend inputs to not create another split (#28387) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45674860 macOS/iOS: macOS Apple Silicon (arm

ggml-cuda: fix divergent barrier in f16 flash attention (#27870) ggml-cuda: fix divergent barrier in f16 flash attention ggml-cuda: avoid duplicate metadata pointer setup Website: https://llama.app At

caps : recheck typed content if template checks for string (#28511) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45690927 macOS/iOS: macOS Apple Silicon

vulkan: support type-aligned GET_ROWS (#28253) vulkan: fall back to CPU for GET_ROWS with misaligned offsets The Vulkan GET_ROWS shader asserts when a tensor's backing-buffer offset plus view_offs is

CUDA: branchless Q4_K/Q5_K unpack to speed up mmvq, L2 prefetch on DGX Spark (#26705) Update Q4_K and Q5_K to use branchless computation, which stops the scale unpack being re-executed for every colum

ggml: add gfx90c HIP support (#26454) ggml: add gfx90c HIP support ggml: make gfx90c HIP support compliant with specifications Website: https://llama.app Attestations: https://github.com/ggml-org/llam

vulkan: add DeepSeek-V4 hyper-connection fused ops (DSV4_HC_COMB/PRE/POST) (#26578) vulkan: add DeepSeek-V4 hyper-connection fused ops (DSV4_HC_COMB/PRE/POST) CUDA has these ops from the DeepSeek-V4 m

tests : initialize the L2_NORM batch array (#28553) tests: bind the L2_NORM batch count to a local GCC cannot prove the loop fills norms up to the index read after it while the bound is a class member

metal : add remaining fa-vec tunings for M2 Max (#28458) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45551940 macOS/iOS: macOS Apple Silicon (arm64) mac

ui : embed assets directly with CMake (#28445) Remove the build-time C++ helper and external gzip dependency, simplifying cross-compilation. Keep the generated C++ in templates for readability and pre

common: add --log-jsonl (#28437) common: add --log-jsonl rename unknown to none Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45560949 macOS/iOS: macOS Ap

grammar : fix max repetition threshold (#28469) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45568343 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple

cuda: fixes races in mmid and mmf (#28475) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45586039 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic

opencl: properly choose weights pack for q4_K, q5_K mul_mat (#28402) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45608946 macOS/iOS: macOS Apple Silicon

[Model] Support for Spark2_5ForCausalLM implementation (#27868) Add Spark3 Model rename spark3 -> spark2_5 Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Co-authored-by: dongjiang d

models : fix GDN normalization from max to rsqrt (#28068) models: use flash-linear-attention's l2norm for gated delta net q/k The GDN q/k normalization is defined by flash-linear-attention as l2norm(x

convert : add --fuse-qkv flag to fuse Q/K/V into QKV during HF-to-GGUF conversion (#22780) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45621954 macOS/iO

sycl: attribute device allocations by site (GGML_SYCL_MEMTRACE) (#27631) define two new environment variables to better understand how much memory is being allocated, and when. This has been invaluabl

sycl : fix test-backend-ops CI break && restore Kronecker product FWHT support (#28016) (#28254) Reapply 'sycl : add Kronecker product FWHT support for sizes 384, 640, 768, 12…' (#28184) This reverts

metal : fix memory leak in early return (#28399) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45438612 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple

SYCL: Refactor GGML_SYCL_ENABLE_MKL_FA to global var (#26863) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45153754 macOS/iOS: macOS Apple Silicon (arm64

sycl: fuse rms_norm+mul+add and add+add residual chains (#27610) Fuse RMS_NORM+MUL+ADD and ADD+ADD under GGML_SYCL_ENABLE_FUSION. ADD+ADD uses the same binbcast indexing and type matrix as standalone

src : add n_expert_used_max function (#28323) src : add n_expert_used_max function With Commit c61b98b ('model: add NVIDIA Nemotron-3-Puzzle-75B-A9B (NemotronHPuzzle) support (#25444)') it is now poss

ggml-cpu(s390x) : fix q5_1 uninitialized v_acc (#28332) Signed-off-by: Aaron Teo aaron.teo1@ibm.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45199911

common : make build info output stream configurable (#28322) Let llama_print_build_info write to a caller-provided FILE* instead of hardcoding stderr. The parameter defaults to stderr so existing call

llama.cpp : bump version to 0.4.0 (#28386) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45314398 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic

opencl: add Adreno xmem SDPA path (#26331) opencl: add Adreno xmem SDPA path Assisted-by: Codex Removed the Adreno-specific queue profiling override Clean up formatting 修复数值误差优化gqa/mask attn Assisted-

opencl: extend the elementwise and data‐movement op coverage (#27633) opencl: add extended elementwise unary ops (sgn, step, elu, hardswish, hardsigmoid, floor, ceil, round, trunc) Adds nine GGML_UNAR

metal : add remaining fa-vec tunings for M3 (#28396) addition of m3 in fa_vec_tuned_table adding q4_0,q4_1,q5_0,q5_1 in ggml-metal-tuning Fix formatting in ggml-metal-tuning.cpp Website: https://llama

In controlled offline evaluations, HydraFusion’s selective coding workflows matched or exceeded the evaluated Opus 5 baseline while reducing estimated workflow cost. Now available as a research previe