llama.cpp has released version b11081, expanding its pre-built binary support to include CUDA 13.4 and ROCm 10.0 for both Linux and Windows platforms. The update also maintains compatibility with existing CUDA 12 builds and continues to feature KleidiAI optimization for Apple Silicon Macs. Internal testing infrastructure has been refined to better handle tensor data standard deviation and recurrent state rollback checks, ensuring stability across diverse model architectures. This release allows developers to run local inference on the latest NVIDIA and AMD GPUs without compiling from source.
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llama.cpp Releases · September 28, 2026 · Same story
llama.cpp Releases · November 7, 2026 · Same story
This release quietly patches a critical memory overflow in the mtmd module that caused crashes when loading HunyuanVL models. The issue stemmed from F64 position embeddings overflowing an F32 buffer, a subtle bug that broke multimodal inference for users relying on this specific architecture. By enforcing strict F32 requirements, llama.cpp stabilizes support for Tencent's vision-language model without adding new features or changing the core API. It’s a necessary maintenance update that keeps local multimodal workflows from breaking unexpectedly.
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.
llama.cpp b11081 release with CUDA 13 and ROCm 10 support
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