Models & Labs
llama.cpp b11221 release with ROCm 10 and CUDA 13
llama.cpp Releaseshigh confidence
Why it matters
- →ROCm 10.0 support allows AMD GPU users to run the latest inference workloads without manual compilation.
- →CUDA 13.4 builds ensure compatibility with NVIDIA's newest driver releases for both Linux and Windows.
- →Snapdragon arm64 support opens local inference possibilities for ARM-based mobile and edge hardware.
llama.cpp has released version b11221, updating its binary distribution to support ROCm 10.0 and CUDA 13.4 across Linux and Windows platforms. The release also adds initial support for Linux arm64 Snapdragon devices, expanding hardware compatibility beyond x86 and Apple Silicon. Notably, KleidiAI builds for macOS Apple Silicon and openEuler configurations have been disabled in this iteration. This update ensures compatibility with the latest GPU driver ecosystems while maintaining broad cross-platform availability.
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Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1llama.cpp b11222 release with ROCm 10 and CUDA 13
llama.cpp Releases · September 28, 2026 · Same story
What happened next
- 2llama.cpp b11739 release with ROCm 10 and CUDA 13
llama.cpp Releases · October 20, 2026 · Same story
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This release quietly closes the hardware gap for local inference by adding default support for CUDA 13 and ROCm 10.0 across Linux and Windows. Users with newer NVIDIA GPUs or AMD accelerators no longer need to compile from source to get performance, while Apple Silicon builds now ship KleidiAI disabled by default, shifting the focus back to standard ARM optimizations. The inclusion of Snapdragon support for Linux and Android marks a significant step toward on-device AI beyond the x86/ARM desktop ecosystem. It is less about new features and more about ensuring llama.cpp remains the universal runtime for every available accelerator.
