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llama.cpp b12022 adds ROCm 10 and Snapdragon support
llama.cpp Releaseshigh confidence
Why it matters
- →ROCm 10 support allows AMD GPU users to run local models without relying on workarounds or older driver versions.
- →Snapdragon Linux support enables direct inference on ARM mobile hardware, reducing reliance on emulation for edge devices.
- →CUDA 13.4 integration ensures compatibility with the latest NVIDIA drivers and hardware generations.
llama.cpp has released version b12022, expanding hardware support for local inference across multiple platforms. Key additions include ROCm 10.0 binaries for Linux and Windows, CUDA 13.4 libraries for both x64 and arm64 architectures, and native Snapdragon support on Linux. The release also provides OpenVINO and SYCL builds for Intel hardware, while disabling KleidiAI on macOS Apple Silicon and openEuler in this specific build. This update broadens the accessibility of llama.cpp beyond NVIDIA GPUs to include AMD, Intel, and ARM-based devices.
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- 1llama.cpp b11113 adds ROCm 10 and Snapdragon support
llama.cpp Releases · September 22, 2026 · Same story
- 2llama.cpp b11935 adds ROCm 10 and Snapdragon support
llama.cpp Releases · October 28, 2026 · Same story
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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.
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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.
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llama.cpp b12027 adds CUDA 13 and Snapdragon support
This release quietly modernizes the local inference stack by adding native support for CUDA 13.4 alongside the existing CUDA 12 builds, ensuring compatibility with the latest NVIDIA driver ecosystems without forcing users to stay on older stacks. The inclusion of ROCm 10.0 and OpenVINO further solidifies llama.cpp as the universal runtime for heterogeneous hardware, while new binaries for Linux arm64 Snapdragon devices bring AI inference to mobile-class ARM silicon. Apple Silicon builds have reverted KleidiAI to disabled by default, a pragmatic choice that prioritizes stability over experimental performance gains for the average user. The result is a more future-proof binary set that removes friction for developers adopting next-generation GPUs and edge processors.
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