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mtmd : fix deprecated strdup warning on Windows (#29863) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/

Qwen4Exp: add MTP (#29761) Qwen4Exp: add MTP remove has_state member, check via ctx_bufs being non-empty consistent naming + less verbose comments cont : clean-up recurrent memory cont : clean-up comm

CUDA: Handle compute type for NVFP4 on cublass path (#29173) CUDA: Handle compute type for NVFP4 on cublass path Signed-off-by: ynankani ynankani@nvidia.com Use BF16 compute type for quantized models

metal : release temporary private transfer buffers (#29777) metal : release temporary private transfer buffers Assisted-by: OpenAI Codex metal : fix order and formatting Co-authored-by: Niklas Wenzel

cuda : route sm70 to the Turing MMVQ nwarps table (#29753) cuda : route sm70 to the Turing MMVQ nwarps table Volta (sm_70) has no MMVQ parameter table of its own and falls through to GENERIC, which la

hexagon: shared strided DMA copy for CPY and CONCAT, any-dim CONCAT via DMA (#29685) hexagon: shared strided DMA copy for CPY and CONCAT, any-dim CONCAT via DMA hex-cpy: various fixes on top of the co

llama : clamp kpool re-pool bound to existing pools (#29805) tests : simplify function signature llama : clamp kpool re-pool bound to existing pools The n_tokens/kpool + n_seqs_unq bound on n_new_g ov

common,rpc : fix cache dir creation through symlinks on buggy libstdc++ (#29816) See https://gcc.gnu.org/bugzilla/show_bug.cgi?id=101510 Close #29759 Signed-off-by: Adrien Gallouët angt@huggingface.co

hexagon: add q2_k and q3_k quant type support (#29717) hexagon: add q2_k and q3_k quant type support hex-qk: consistent allocation of src1_row_size Co-authored-by: Max Krasnyansky maxk@qti.qualcomm.co

hexagon: install rebuilt HTP skels (#29828) hexagon: install rebuilt HTP skels Assisted-by: OpenCode hexagon: fix HTP skel catalog dependencies Assisted-by: OpenCode Website: https://llama.app Attesta

ggml : add alloc_buffer_n to buffer type interface (#23671) ggml : add alloc_buffer_n to buffer type interface Add alloc_buffer_n method to ggml_backend_buffer_type_i interface, with a public API ggml

qwen4exp : optimize mask constructions (#29824) qwen4exp : optimize mask constructions cont : apply the same change for GLM5-next Website: https://llama.app Attestations: https://github.com/ggml-org/l

vulkan: disable large matmul tile on Samsung GPUs with 32KB shared memory (#28531) Assisted-by: Claude Opus Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/

llama, server: add /v1/systemone API (models: laya, julia-1, lev, openjev, kev) (#29818) init conversion convert: ok model loaded add server code improve conversion script support shared prompt prefix

arXiv:2610.01184v1 Announce Type: cross Abstract: Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive con

Hi folks, I'm a long-time lurker and big fan of this subreddit and a massive self-hosting fan (also outside of AI). I doubt many people will disagree with me here because I see the same arguments bein

llama : preserve original batch order for speculative decoding layer inputs (#29019) llama: preserve original batch order for layer inputs Assisted-by: Codex tests: cover layer-input order across KV l

args: fix cli download mmproj arg (#28977) tests: add tests for cli download arg parsing args: fix cli download mmproj arg Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cp

Hexagon: optimize ALLREDUCE with support for safe scatter mode (#29757) hex-allreduce: add support for safe scatter mode hex-allreduce: pare down excessive comments hex-allreduce: re-write to remove r

cuda: guard the iq4_nl dequantize row kernel against short rows (#29683) dequantize_block_iq4_nl writes QK_K values per block, but a row can be shorter than that (an IQ4_NL row is only guaranteed to b

ggml-opencl : replace alloca() with std::vector (#29765) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/

model : re-enable -sm tensor for qwen4exp (#28569) #27941 disabled -sm tensor for qwen4exp because test-llama-archs asserted on the Meta device once the fixture carried a PLE layer: GGML_ASSERT(ggml_b

llama-bench : fix verbosity filter to show GGML_LOG_ERROR (#28229) bench : fix verbosity filter to show GGML_LOG_ERROR (#28107) bench: remove dead variables Website: https://llama.app Attestations: ht

vocab : honor BOS/EOS settings for PLaMo-2 and PLaMo-3 (#29734) vocab : honor BOS/EOS settings for PLaMo-2 and PLaMo-3 The original tokenizer configs for PLaMo-2 and PLaMo-3 have add_bos_token: true a

common : add LLM-jp-4.1 Harmony dialect handler (#29681) LLM-jp-4.1 uses the GPT-OSS format, but its tokenizer decodes a space after every special token and parallel tool calls are separated by <|end|

BLAS : Document AOCL-BLAS build and label the device AOCL-BLAS (#29640) BLAS : Document AOCL-BLAS build and label the device AOCL-BLAS AOCL-Blas : Add an AOCL-BLAS Quick Start and drop the fixed versi

hex-workqueue: fix race condition in seqn getting out of sync with idx_read/write (#29785) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51906249 macOS/iO

HIP: avoid treating CDNA as dgx spark for gqa_ratio 20 in fattn_mma dqk 576 (#29572) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51919562 macOS/iOS: mac

llama-mmap : avoid a second full-size copy of each tensor with direct-io (#29749) Assisted-by: Claude Co-authored-by: Pranesh Gonegandla pgonegandla@nvidia.com Website: https://llama.app Attestations:

arXiv:2609.38294v1 Announce Type: new Abstract: We study the generation of agentic workflows that jointly optimize multiple objectives, such as accuracy, cost, latency, robustness, and consistency. Ex

vulkan: Tune GDN kernel, fix Intel performance (#29476) vulkan: tune GDN shader tune for Intel Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51306598 macO

ci: add zdnn backend build but not test (#29541) ci: add zdnn backend build but not test Signed-off-by: Aaron Teo aaron.teo1@ibm.com ci: attempt to run a ubuntu 26.04 container Signed-off-by: Aaron Te

ggml-cuda: HIP: optimize packed byte subtraction (__vsubss4 -> __vsub4) (#29478) ggml-cuda: HIP: optimize non-saturating packed byte subtraction (__vsubss4) CI: ignore 1 spilled vgpr in fattn_vec Co-a

hexagon: optimize concat op (#29673) hex-concat: reduce pkts in gather/transpose hot loop gather directly into dst buffer, use special instruction for gather sync hex-concat: use fastdiv replace calls

model : support classifier_pooling for rerankers (#29627) model : support classifier_pooling for ModernBERT rerankers Assisted-by: Claude Opus 5.5 model : read classifier pooling type in load_hparams

ggml : check row bounds in get_rows_back (#29575) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/5139241

gguf : reject tensor size that wraps after padding (#26979) GGML_PAD(nbytes, alignment) wraps to 0 when nbytes is within (alignment - 1) of SIZE_MAX, which silently bypassed the size overflow guard in

Hexagon f16 activation ops (#29209) hexagon: add F16 support for activation ops (SILU/GELU/GELU_QUICK/GEGLU/SWIGLU) Widens ggml_hexagon_supported_activations() to accept F16 (src0/dst/src1 must agree

ggml-zdnn: impl buffer reset, fix memory leaks (#29637) cont: fix code style Signed-off-by: Aaron Teo aaron.teo1@ibm.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/

add GLM-5.3-Flash (GLM5-Next) support (#27773) Rebase GLM-Next support onto master, and migrate to llama-memory-hybrid-idx Add initial MTP support Merge branch optimizations. Reduce allocated compute

musa : define CUDA_ARCH for device passes (#29508) The MUSA vendor header never defined CUDA_ARCH, so every architecture test in the shared ggml-cuda sources evaluated to 0. Kernel bodies gated on the

openvino: serve GET_ROWS on a weight view from the base Constant (#28381) openvino: serve GET_ROWS on a weight view from the base Constant Resolve view_src when collecting weight Constants so a view o

cpu: accept BF16 in src1 of mul_mat (#28937) cpu: accept BF16 in src1 of mul_mat ggml_conv_1d_dw builds its im2col in F32 when the kernel is BF16, then calls ggml_mul_mat(im2col, kernel), which puts F

ggml : add BF16 unary, GLU, binary and scale ops (CPU, CUDA) (#29675) ggml : add BF16 unary, GLU, binary and scale ops (CPU, CUDA) ggml-cpu : use per-op _bf16 functions for BF16 unary and GLU ops Assi

llama: llama_prefetch_rows (#29599) llama: llama_prefetch_rows llama: support row prefetch on Windows Apply the Windows port contributed by @praneshgo unchanged. Source: #29599 (comment) avoid exposin

ci : fix Models Backend Check by shortening the hrm_text fixture (#29744) The fixture recycles its two blocks over 8 cache slots, so the fp16 error builds up past the 1e-4 NMSE bound on the Vulkan T4