github llama.cpp · just now · inference

llama.cpp b10742 adds fa-vec tunings for A18 Pro

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The llama.cpp project has released version b10742, which includes a new feature adding fast vector (fa-vec) tunings specifically for the Apple A18 Pro chip found in the MacBook Neo.

This release provides binaries across multiple platforms and hardware configurations:

macOS: Apple Silicon (arm64), Intel (x64), and iOS XCFramework.
Linux: Ubuntu builds for CPU (x64, arm64, s390x), Vulkan, ROCm 7.14, OpenVINO, and SYCL (FP32/FP16).
Windows: CPU (x64, arm64), OpenCL Adreno, CUDA 12/13, Vulkan, OpenVINO, SYCL, and ROCm 7.14.
Android: arm64 CPU.

The release notes indicate that KleidiAI support for macOS Apple Silicon is currently disabled in this build.

Importance 1/3 Trust 1/3 llama.cpp Inference efficiency Local inference

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github llama.cpp · 3h ago · 1 view

llama.cpp b10739 adds fa-vec tuning for M2 Max

The llama.cpp project has released version b10739, which includes a specific performance optimization for Apple's M2 Max hardware. This update introduces fast attention vector (fa-vec) tuning tailored to the M2 Max's 30 GPU cores.

lab Hugging Face Blog · 3h ago · 3 views

Hugging Face releases 207 WebGPU kernels and a browser benchmarking tool

Hugging Face has released @huggingface/kernels, a library for loading and running optimized WebGPU kernels from the Hugging Face Hub, alongside an initial collection of 207 kernels. The release also introduces Fleet, an in-browser GPU benchmarking suite that crowdsources performance and correctness evidence from users' devices.

github llama.cpp · 7h ago · 1 view

llama.cpp b10739 adds fa-vec tuning for M2 Max

Hugging Face releases 207 WebGPU kernels and a browser benchmarking tool

llama.cpp b10734 enables Metal 4.0 tensor API on M5+/A19+

ExLlamaV3 adds CPU offload for MoE experts and new GLM-5.3-Flash, Qwen3.8-Flash models

llama.cpp b10724 optimizes kv-cache state restore to reduce copy count from 1.3M to 224