Model Releases
b11160
vulkan: int8 coopmat1 matmul implementation for AMD RDNA3 and RDNA4 (#27952) vulkan: add int8 coopmat quantized matmul shader apply scales inline use scalar sums probe and directly access coopmat valu
vulkan: int8 coopmat1 matmul implementation for AMD RDNA3 and RDNA4 (#27952) vulkan: add int8 coopmat quantized matmul shader apply scales inline use scalar sums probe and directly access coopmat values instead of going through shmem add q8_0 support add BK_STEP to shader, default to 2 use larger workgroups double buffering preload scales coopmat load first, then wmma use float for scales add faster RDNA int->float conversion workgroup scheduling for cache proximity clean up use wave32 restructure for vgpr use skip computation for inactive tiles only force subgroup size 32 on AMD RDNA use BK_STEP 4 fix compilation move quant-specific prefetch function out of main file add q4_1, q5_0, q5_1 support restructure mmq cm1 functions enable mul_mat_id support fix segfault fix mul_mat_id bug support iq4_nl and mxfp4 remove elem row/col fast path, invalid for RDNA4 use shmem arrays for LUTs use 4-byte loads where possible add q3_k, q4_k, q5_k, q6_k and nvfp4 support fix l warptile improve performance improve performance improvements dedup b scales merge shmem arrays undo uint8_t, gate to RDNA3/4 add RDNA4 architecture, use for hardcoded coopmat elem thread access, set BK_STEP back to 4 improve offset application clean up fix iq4_nl and nvfp4 performance rdna4 tuning use BK_STEP 2 on MUL_MAT_ID adapt to upstream changes fix shmem support function, clean up comments fix warptile logic Co-authored-by: Piotr Wilkin (ilintar) piotr.wilkin@syndatis.com vulkan: add IQ4_XS support to the coopmat1 integer matmul shader (#28440) Adds IQ4_XS to mul_mmq_cm1: dedicated block_a_load/block_a_to_shmem that expand both nibbles of each packed32 word through cm1_kvalues, LOAD_VEC_A 8 and an IQ4_XS-sized a_panel_bytes estimate for the L2-friendly scheduling. Assisted-by: OpenAI Codex Co-authored-by: Claude Opus 5 (1M context) noreply@anthropic.com avoid compiling f16 acc shader variants Co-authored-by: Piotr Wilkin (ilintar) piotr.wilkin@syndatis.com Co-authored-by: Claude Opus 5 (1M context) noreply@anthropic.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49867492 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) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI
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Source: llama.cpp Releases | 2026-09-24