Models & Labs
llama.cpp b9010 Release Fixes CUDA Multi-GPU Issue
llama.cpp Releaseshigh confidence
Why it matters
- →Fixes critical multi-GPU support issue, enhancing performance for CUDA users.
- →Expands compatibility across various platforms, including Apple Silicon and Vulkan.
- →Improves stability and reliability of llama.cpp for diverse hardware setups.
The b9010 release of llama.cpp resolves a significant issue with CUDA device PCI bus ID detection that led to out-of-memory errors by ignoring additional GPUs. This fix enhances multi-GPU support, particularly benefiting users on Windows platforms. The update also includes platform-specific improvements for macOS, Linux, and Windows, with notable support for Apple Silicon and Vulkan. This release focuses on improving stability and compatibility rather than introducing new features.
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Llama.cpp adds GLM-5.2 speculative decoding support
Llama.cpp's latest update introduces speculative decoding support for GLM-5.2, enhancing its capabilities with NextN/MTP features. This addition allows for more efficient tensor loading and context management, particularly benefiting models using the GLM_DSA architecture. The update also includes options for exporting models with or without the MTP feature, providing flexibility for developers. This release marks a step forward in optimizing model performance and adaptability, especially for those leveraging the GLM-5.2 framework.
llama.cpp Releases
Open Sourcemodels
llama.cpp b10175 Release Expands Platform Support
The latest b10175 release of llama.cpp continues its trend of broadening platform compatibility, making it a versatile tool for developers across different systems. Notably, this update includes support for ROCm 7.2 on Ubuntu x64, which is significant for AMD GPU users seeking alternatives to NVIDIA's CUDA. The release also maintains a wide array of builds for Windows, macOS, and Linux, ensuring that developers can leverage llama.cpp's capabilities regardless of their hardware setup. While there are no groundbreaking new features, the consistent expansion of platform support solidifies llama.cpp's position as a flexible inference runtime option.
