Models & Labs
llama.cpp b11747 adds ROCm 10 and CUDA 13 support
llama.cpp Releaseshigh confidence
Why it matters
- →ROCm 10.0 support allows AMD GPU users to run local inference without manual compilation.
- →CUDA 13.4 binaries prepare the ecosystem for next-generation NVIDIA hardware releases.
- →Multi-platform coverage solidifies llama.cpp as the standard runtime for diverse AI accelerators.
llama.cpp has released build b11747, expanding hardware compatibility with new binaries for ROCm 10.0 and CUDA 13.4. The update adds AMD ROCm support to both Linux and Windows platforms, addressing a long-standing gap for users of Radeon GPUs. NVIDIA users gain access to CUDA 13.4 libraries alongside existing CUDA 12 builds, ensuring forward compatibility with newer hardware architectures. Additionally, the release includes updates for OpenVINO, SYCL, and Snapdragon AI engines, while temporarily disabling KleidiAI support on macOS Apple Silicon.
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- 1llama.cpp b11799 adds ROCm 10 and CUDA 13 support
llama.cpp Releases · October 22, 2026 · Same story
- 2llama.cpp b11848 adds ROCm 10 and CUDA 13
llama.cpp Releases · October 24, 2026 · Same story
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Open the full story →llama.cpp b11747 adds ROCm 10 and CUDA 13 support
3 developments
- Oct 20 · llama.cpp Releases
llama.cpp b11747 adds ROCm 10 and CUDA 13 support (This article) - Oct 28 · llama.cpp Releases
llama.cpp adds LiquidAI d1 models and CUDA 13 support↳ llama.cpp adds native support for LiquidAI d1-2B and d1-omni-2B models - Oct 28 · llama.cpp Releases
llama.cpp adds LiquidAI LFM3-Audio and Omni support↳ llama.cpp adds native conversion for LiquidAI LFM3-Audio and Omni architectures with specific encoder convolution handling
More from llama.cpp Releases
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llama.cpp b12022 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing ROCm 10.0 to Linux and Windows alongside CUDA 13.4, effectively closing the hardware gap for AMD users who were previously left behind. The inclusion of native Snapdragon support on Linux marks a significant step toward running local LLMs on ARM-based mobile chips without emulation overhead. While KleidiAI on Apple Silicon is disabled in this build, the broader expansion to diverse accelerators ensures that developers aren't locked into NVIDIA ecosystems anymore.
llama.cpp Releases
Coding Toolscoding
llama.cpp b12023 fixes shared prefix bug
This release addresses a specific inference artifact where decision prefixes were incorrectly bleeding into output embeddings. By capping shared prefixes at the first output position, llama.cpp ensures that option tokens remain distinct for parent and child tasks. This is a targeted fix for multi-step reasoning or voting workflows rather than a performance boost. It stabilizes complex generation patterns without changing the underlying model architecture.
llama.cpp Releases
Coding Toolscoding
llama.cpp b12024 adds Snapdragon and ROCm 10
This release quietly expands llama.cpp's hardware support to include Qualcomm Snapdragon devices with CPU, Adreno GPU, and Hexagon NPU acceleration. It also updates ROCm to version 10.0 for both Linux and Windows, keeping AMD users in step with the latest driver stack. CUDA builds now default to 13.4 libraries alongside 12.x options, reflecting the industry's gradual shift toward newer NVIDIA toolkits. While no new model architectures are introduced, the binary matrix grows significantly, ensuring local inference remains viable on a wider array of edge and server hardware.
llama.cpp Releases
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