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llama.cpp b11011 expands AMD and Apple Silicon support
llama.cpp Releaseshigh confidence
Why it matters
- →ROCm 10.0 support allows AMD GPU users to run local models without relying on workarounds or older driver versions.
- →CUDA 13 builds provide forward compatibility, ensuring the runtime works with next-generation NVIDIA hardware and drivers.
- →The release solidifies llama.cpp's role as a cross-platform standard, reducing fragmentation for developers deploying models on non-NVIDIA chips.
llama.cpp has released version b11011, a significant update focused on expanding hardware compatibility across Linux, Windows, and macOS platforms. Key additions include ROCm 10.0 support for AMD GPUs on both Linux and Windows, as well as CUDA 13 builds (12.8/13.3) to ensure future-proofing for NVIDIA users. The release also maintains extensive CPU support via OpenVINO and SYCL, while explicitly disabling KleidiAI for macOS Apple Silicon binaries in this specific build. This update reinforces llama.cpp's position as the go-to engine for local LLM inference across diverse hardware ecosystems.
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llama.cpp b11000 fixes critical RCE in server
This release patches a critical remote code execution vulnerability in the llama.cpp server that allowed unauthenticated attackers to hijack memory via dangling pointers. The flaw stemmed from caching compute graphs that referenced freed buffers, enabling heap corruption and arbitrary code execution through subsequent tensor commands. By discarding cached graphs when buffers are freed, the fix forces a safe fallback to full recomputation without changing the API. This is a vital security update for anyone running the llama.cpp server remotely, closing a direct path to system compromise.
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llama.cpp b11001 fixes Spacemit transpose bug
A copy-paste error in llama.cpp was corrupting matrix transpositions on Spacemit hardware, causing significant data corruption for int16 operations. This release patches the specific RVV instruction call to ensure correct computation on these RISC-V based chips. While niche, it prevents silent inference failures for users relying on this specific accelerator architecture. The update also ships binaries for CUDA 13 and ROCm 10.0, keeping the runtime current with latest driver ecosystems.
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