github

<details open> vulkan: add fwht support for Intel with shmem reduction (#23964) * vulkan: add fwht support for Intel with shmem reduction * don't use N as workgroup size * disable subgroup shuffle on MoltenVK AMD * disable fwht shader on Intel Windows due to driver bug </de

<details open> model: fix build failed (#24193) </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9533/llama-b9533-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github

<details open> TP: round up granularity to 128 (#24180) * TP: round up granularity to 128 * remove assert </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9531/llama-b9531-bin-macos-arm64.tar.gz) - macOS Apple

<details open> cli: fix model params not propagated (#23893) Fixes #23847 </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9530/llama-b9530-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled

<details open> model : fix llama_model::n_gpu_layers() (#24188) </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9529/llama-b9529-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED

<details open> ui: run npm install when package-lock.json is newer than node_modules (#24171) </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9528/llama-b9528-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm6

## Highlights This release features 8 commits from 6 contributors (1 new)! v0.22.1 is a patch release on top of v0.22.0 with targeted bug fixes plus a couple of additions: new model support for JetBrains' Mellum v2, zentorch-accelerated quantized linear inference on AMD Zen

<details open> minor : fix lint issues (#24165) </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9524/llama-b9524-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github

<details open> hparams : refactor `hparams.n_layer` (#24060) * hparams : refactor hparams.n_layer * cont : remove `n_layer_kv()`, use n_layer_all instead * cont : type consistency * pi : update SYSTEM.md * models : fix Step3.5 MTP * cont : remove duplicate switch cases *

<details open> kleidiai : dynamic chunck-based scheduling for hybrid execution (#23819) </details> **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b9522/llama-b9522-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, Kle

<details open> CUDA: enroll mul_mat_vec_q_moe into pdl (#24087) * Enroll mul_mat_vec_q_moe into PDL, boosting MTP performance on BW Data collected on a B4500: Before ``` (llama.cpp) ➜ llama.cpp git:(master) ✗ python mtp-bench.py code_python pred= 192 draft= 150 acc=

<details open> sycl : port multi-column MMVQ from CUDA backend (#21845) mmvq: Port the ncols_dst optimization from ggml-cuda/mmvq.cu to SYCL. Read weights once per dispatch instead of once per column. Covers all standard quant types + reorder paths for Q4_0, Q8_0, Q3_K, Q4_K,

# Patch release v5.10.2 There was a big bug in the model conversion of models related to clip, this affected models like sam3 and others. Please make sure to update :pray: * Fix conversion for clip models by @zucchini-nlp (#46406) **Full Changelog**: https://github.com/