llama.cpp has released version b12024, adding support for Qualcomm Snapdragon platforms with CPU, Adreno GPU, and Hexagon NPU acceleration. The update also upgrades ROCm support to version 10.0 across Linux and Windows builds. CUDA binaries now include libraries for both CUDA 12.8 and the newly added CUDA 13.4. Additional builds cover openEuler with ACL Graph support for Huawei Ascend chips and various OpenVINO configurations.
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llama.cpp Releases · September 26, 2026 · Same story
llama.cpp Releases · October 2, 2026 · Same story
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.
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.
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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