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llama.cpp b11146 adds CUDA 13 and Snapdragon support
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Why it matters
- →CUDA 13 support allows developers to test inference on the latest NVIDIA driver stacks before they become standard.
- →Snapdragon arm64 binaries enable local AI execution on high-performance mobile and edge devices with NPU acceleration.
- →Continued openEuler integration ensures compatibility with Chinese domestic hardware ecosystems like Huawei Ascend.
llama.cpp has released build b11146, expanding hardware compatibility for local inference. The update adds native support for CUDA 13.4 on Ubuntu and Windows for both x64 and arm64 architectures, alongside ROCm 10.0 builds. A key addition is the first official Linux arm64 binary targeting Snapdragon platforms, supporting CPU, Adreno GPU, and Hexagon NPU acceleration. The release also includes updates for openEuler with ACL Graph support for Huawei Ascend chips. macOS KleidiAI builds are currently disabled in this version.
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llama.cpp b11140 optimizes sparse attention on CUDA
This release targets a specific bottleneck in long-context inference by optimizing the sparse flash attention prefill step for NVIDIA GPUs. By templating kernels to unroll loops at compile time, batched sparse operations drop from 586 microseconds to 244 microseconds on 49k context windows. This isn't just a generic speed bump; it makes handling very long documents significantly more efficient for users relying on sparse attention mechanisms. The change is already baked into the standard CUDA builds, requiring no special flags.
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llama.cpp b11147 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing first-class ROCm 10.0 support to both Linux and Windows. AMD GPU users no longer need workarounds, effectively closing a long-standing parity gap with NVIDIA's CUDA ecosystem. Equally notable is the new Linux arm64 build targeting Snapdragon chips, which unlocks local LLM execution on high-performance mobile hardware via CPU, Adreno GPU, and Hexagon NPU acceleration. While KleidiAI on Apple Silicon has been disabled in this specific binary set, the broader platform expansion signals a shift toward heterogeneous computing that extends well beyond traditional desktop GPUs.
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llama.cpp b11149 adds backend testing and ROCm 10 support
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