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llama.cpp b11147 adds ROCm 10 and Snapdragon support
llama.cpp Releaseshigh confidence
Why it matters
- →ROCm 10.0 support removes the last major barrier for AMD GPU users running local inference.
- →Snapdragon arm64 builds enable efficient LLM execution on mobile hardware using Hexagon NPU acceleration.
- →Continued parity in CUDA 12/13 and Vulkan support ensures broad compatibility across diverse hardware setups.
llama.cpp has released version b11147, expanding hardware compatibility with significant additions for AMD and mobile platforms. The update includes ROCm 10.0 builds for Ubuntu x64 and Windows x64, addressing a key limitation for non-NVIDIA users. Additionally, new Linux arm64 binaries now support Snapdragon processors, leveraging CPU, Adreno GPU, and Hexagon NPU acceleration. macOS Apple Silicon (arm64) builds are available, though KleidiAI optimization is currently disabled in this release. The update also maintains support for CUDA 12/13, Vulkan, OpenVINO, and SYCL across major operating systems.
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llama.cpp b11146 adds CUDA 13 and Snapdragon support
The latest llama.cpp build brings immediate relevance to users on bleeding-edge NVIDIA hardware with native CUDA 13.4 support across Linux and Windows, closing the gap for those testing next-gen GPU architectures. More notably, it finally addresses the mobile inference landscape by including a dedicated build for Linux arm64 Snapdragon devices, covering CPU, Adreno GPU, and Hexagon NPU paths. This moves local AI beyond just desktop GPUs into the realm of high-performance edge computing on Qualcomm silicon. While Apple Silicon builds have KleidiAI disabled in this specific release, the expansion to ARM-based mobile NPUs marks a significant shift in where llama.cpp can run efficiently.
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