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llama.cpp b9297 release enhances tensor support

The b9297 release of llama.cpp brings a notable enhancement with the introduction of NVFP4 MTP scale tensors, boosting its tensor processing capabilities. This update also integrates Qwen3.5 MTP tensors, which improves performance across a spectrum of hardware configurations, including Apple Silicon, Vulkan, and ROCm on Ubuntu, as well as CUDA on Windows. The release supports a wide array of architectures, from macOS to Linux and Windows, ensuring compatibility with both CPU and GPU setups. While there are no new model architectures, the inclusion of KleidiAI on Apple Silicon and ROCm 7.2 on Ubuntu highlights llama.cpp's commitment to optimizing for diverse environments. This update reinforces llama.cpp's role as a flexible inference runtime, catering to a broad range of hardware setups.

llama.cpp b9309 release fixes integer overflows

The b9309 release of llama.cpp tackles significant integer overflow issues in its perplexity calculations, co-authored by Stanisław Szymczyk. This update is vital for enhancing the accuracy and reliability of the model's performance metrics, which are crucial for developers. By resolving these overflows, the release ensures that users can depend on precise data outputs. This fix is a testament to the ongoing efforts to improve the tool's robustness, allowing developers to trust the integrity of their AI computations. While it might seem like a minor adjustment, it plays a critical role in maintaining the tool's reliability.