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§ local-llm · storyline

Speeds up Metal inference with tensor flash attention kernels

Metal speeds up inference with tensor flash attention kernels.

Oct 3 · · primary fetch1 sourceupdated Oct 3 ·

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 attention sinks, ALiBi and logit softcap in the tensor FA kernel cont : add tensor FA kernel for DK=192, DV=128 Website: Attestations: macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Android: Android arm64 (CPU) Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.4 DLLs Windows arm64 (CUDA 13) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows x64 (OpenVINO)…

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§ sources1 publication · timeline below
  1. github.comllama.cpp b11362primary