All entries

metal : few-row MMA mat-mul (#29869) metal : few-row MMA mat-mul and batched copies for speculative decoding Speculative decoding verifies a few draft tokens per step. Without the tensor API, Metal ra

cuda: tile the lightning indexer over keys and tokens for 4 heads (#29901) cuda: tile the lightning indexer over keys and tokens for 4 heads With too few heads for a wmma tile, a block scores 64 keys

webgpu: add MMVQ support for Q1_0/Q5_0/Q5_1/Q3_K/Q5_K/Q6_K/MXFP4 (#29483) add supports for q1/q5/q3_k/q5_k/q6_k/mxfp4 of mmvq path Add K_QUANTS_HANDLING macro to q1_0 of mmvq path Website: https://lla

vulkan : Fix undeclared identifiers when -DGGML_VULKAN_RUN_TESTS=ON (#29912) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52752005 macOS/iOS: macOS Apple

ggml-cpu : add Q8_0 IME1 matrix kernel for SpacemiT X60 (#28479) ggml-cpu : add Q8_0 IME1 matrix kernel for SpacemiT X60 On the SpacemiT X60, IME matrix acceleration only covered Q4_0/Q4_1/Q4_K. Q8_0

kv-cache: fix restoring mismatched KV cache rotation by saving exact rotation metadata (#28498) kv-cache: save exact KV rotation metadata, reject restoring mismatched rotation tests : move the state r

llama : fix unexpected graph reallocation in the k-pool models (#29958) llama : fix unexpected graph reallocation in the k-pool models Both k-pool models built a graph shape that depends on state the

vulkan: sparse flash attention for quantized K/V (#29639) vulkan: sparse flash attention for quantized K/V Assisted-by: Claude vulkan: single-scan sparse FA index compaction The compaction ran one wor

vulkan: fix stale prealloc_y reuse across flash attention and soft_max (#29591) Assisted-by: Claude Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52808438

server: reject partial media truncation (#24076) server: reject partial media truncation server: keep only the keep_first fix Drop the mtmd test helper change, which no longer builds since clip_image_

CUDA: Optimize accumulation in mmq for NVFP4 type (#29857) ggml_cuda: optimize accumulation in mmq_vec_dot_fp4_fp4_mma for better performance remove whitespace fix: correct indentation in mma_block_sc

server: support vision input for Clef (#29969) server: support vision input for Clef move input_attn_causal to private extend old server_batch::embd server_batch::token::pos to multi dim nits fix abor

vulkan: fix Flash Attention shmem write out of bounds (#29988) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52864580 macOS/iOS: macOS Apple Silicon (arm6

llama.cpp : bump version to 0.6.0 (#29997) llama.cpp : bump version to 0.6.0 scripts : update summary prompt (#0) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attesta

hexagon: matmul and flash-atten scalability updates (#29974) hexagon: head-parallel flash_attn partitioning for row-split multicore In row-split mode each core computes its output row shard of every M

hexagon: add pool op support (#29995) hexagon: add pool_2d support hexagon: add pool_1d support hex-pool: dma changes hex-pool: Optimize HTP pooling boundaries and DMA pipelining hex-pool: code cleanu

We’re launching ReviewBench, a benchmark for code review agents built on representative GitHub pull requests, multi-source ground truth, calibrated evaluation, and production-aligned metrics. The post

Overview llama.cpp v0.6.0 introduces the new llama_batch_ext extended batch API (with llama_process) for mixed token/embedding inputs and MTP/deepstack state embeddings, adds support for the GLM-5.3-F

webgpu: add f16 support to fill/set_rows (#29897) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52497832 macOS/iOS: macOS Apple Silicon (arm64) macOS Appl

ci : pushing tag needs deploy key (#29937) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52545484 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic

common : prepare load_from_models_dir() for path conversion (#29674) This is part of the fs::path modernization series. That was also the opportunity to remove fs_list(). Signed-off-by: Adrien Gallouë

spec : fix n-gram drafts rejected at temp > 0 after truncation (#29924) Co-authored-by: Pranesh Gonegandla pgonegandla@nvidia.com Website: https://llama.app Attestations: https://github.com/ggml-org/l

imatrix: calculate activation-based statistics for new format (GGUF) imatrices (#14891) Use activations to calculate the stats Determine calculation mode Compute entropy for activations Compute cosine

vulkan: fix rdna4 mat_vec tuning (#29934) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52579133 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silico

CUDA: fix MMQ memory fault if n_expert >> n_ubatch (#29941) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52581427 macOS/iOS: macOS Apple Silicon (arm64)

cuda : move blocks_per_col to where it is used (#29939) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/5

ci : set default permissions (#29945) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52595372 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (a

chat-peg-parser : clear current_tool when pending_tool_call is reset (#29942) A TOOL_ID node that arrives after TOOL_CLOSE wrote through current_tool, which still pointed into the just-destroyed pendi

ci : windows llvm build requires ninja multi-config (#29959) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52619546 macOS/iOS: macOS Apple Silicon (arm64)

cuda : move neu_padded to where it is used (#29940) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52636

ggml-cpu: support BF16/FP16/FP32 K tails in tinyBLAS on x86 (#29806) ggml-cpu: vectorize BF16 K tails in tinyBLAS tests: Skip tinyBLAS when use_ref is enabled so CPU tests compare against the vec_dot

What's Changed Models run on MLX on Apple Silicon by default In this release, on Apple Silicon devices, model architectures supported by the MLX runtime will automatically run on MLX. ollama pull qwen

mlx: match publisher tokenizer semantics Honor pretokenizer stage order, split behavior, Unicode boundaries, added-token normalization, and ranked BPE merges. Handle empty added tokens and empty Metas

metal : add tensor API flash attention kernel for F16 KV (#29570) metal : add tensor API flash attention kernel for F16 KV cont : add tensor FA kernels for DK=DV=512 and DK=576, DV=512 cont : support

model: support nimble decision model (#29844) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52332773 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Si

ggml-cpu : fix soft_max_back wrong output when dst aliases src1 (#27096) ggml-cpu : fix soft_max_back wrong output when dst aliases src1 GGML_OP_SOFT_MAX_BACK is listed in ggml_op_can_inplace, so the

ggml-quants : avoid invalid rounding in qkx3 scale search (#29817) ggml-quants : avoid invalid rounding in qkx3 scale search The imatrix scale search can produce an infinite, NaN, or otherwise out-of-

spec : add probabilistic sampling for simple draft and MTP (#27694) Make the drafter probabilistic and the target verify by rejection sampling Drop stale spec_draft_q before drafting Fallback to argma

CUDA: fuse shared experts into MMVQ (#29184) CUDA: fuse shared experts into MMVQ check if buffer is null move stride_col_dst to fusion args Website: https://llama.app Attestations: https://github.com/

model: add support for clef decision model (text-only) (#29831) init support for clef (text only) more static graph clean up nits nits 2 Update gguf-py/gguf/constants.py Co-authored-by: Sigbjørn Skjær

qwen4exp : halve the indexer score memory (#29825) qwen4exp : halve the indexer score memory The indexer scored all heads in one product and rectified a copy of it, so two [n_pool, n_idx_h, n_tokens]

ggml-openvino: update to 2026.4.1, optimize performance, expand ops, improve device listing. (#29852) ggml-openvino : Qwen3.5 MoE perf (#312) Squash of ravi9#312: ggml-openvino: add detailed inference

graph: gather the recurrent states once so the reserve covers every split (#29856) build_rs gathered the extra states (n_rs - n_seqs rows) with their own get_rows. The worst-case reserve has n_rs == n

ci: fix flaky ADD_ADD f16 by using the fused ADD tolerance (#29904) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52418791 macOS/iOS: macOS Apple Silicon

chat : honor json_schema in Ling 3.0 parser (#29813) chat : honor json_schema in Ling 3.0 parser Ling 3.0 only built a grammar for tool calls and did not handle inputs.json_schema, so response_format

common : add common_is_tty() helper and fix deprecated warnings on Windows (#29860) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-