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llama.cpp b11104 adds multi-addr server binding
llama.cpp Releaseshigh confidence
Why it matters
- →Enables flexible network routing for local LLM servers behind proxies.
- →Removes single-address constraint, simplifying complex deployment topologies.
- →Includes updated CUDA 13 and ROCm 10.0 binaries for broader hardware support.
llama.cpp has released version b11104, introducing support for binding the llama-server to multiple network addresses. This update allows users to expose the inference endpoint on various interfaces simultaneously, simplifying integration with reverse proxies and local development environments. The release also includes updated binaries supporting CUDA 13.4 and ROCm 10.0 across Linux and Windows platforms. Existing features like KleidiAI on Apple Silicon remain available but are not the primary focus of this specific patch.
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llama.cpp b11105 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing full ROCm 10.0 support to both Linux and Windows, closing a long-standing gap for AMD GPU users who previously had to rely on workarounds or older versions. The inclusion of CUDA 13 builds alongside CUDA 12 ensures compatibility with the latest NVIDIA driver stacks without forcing users into beta territory. Perhaps most notably, the addition of native Snapdragon support on Linux marks a significant step toward efficient AI inference on ARM-based mobile and edge devices, expanding the hardware ecosystem beyond traditional x86 and NVIDIA dominance.
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llama.cpp b11108 adds ROCm 10 and Snapdragon support
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