Model Releases
b10241
CUDA: Fix data-races when reusing SMEM in block_reduce (#26385) CUDA: Fix data-races when reusing block_reduce block_reduce currently doesn't resync after reading from SMEM, causing potential data-rac
CUDA: Fix data-races when reusing SMEM in block_reduce (#26385) CUDA: Fix data-races when reusing block_reduce block_reduce currently doesn't resync after reading from SMEM, causing potential data-races when reusing SMEM for multiple reductions. One may consider simply always adding this in block_reduce, but this comes at a potential perf cost double-buffering for single-row softmax double-buffering for norm as well Add comment Add explanatory comment to block_reduce Specify need for + do memory barrier only in multi-warp scenario Implement review-suggestion from @gaugarg-nv Website: https://llama.app 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 (ROCm 7.2) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Android: Android arm64 (CPU) Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.3 DLLs Windows x64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (HIP) 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 | 2026-08-03