Models & Labs
Llama.cpp b10178 Release Adds Trace Logging
llama.cpp Releaseshigh confidence
Why it matters
- →Trace logging provides developers with deeper insights into system operations.
- →Enhanced platform support broadens the tool's applicability.
- →No new models, but improved infrastructure for existing users.
Llama.cpp has released version b10178, which includes new trace logging capabilities for slot similarity checking in server-context.cpp. This feature provides detailed logs on skip reasons and similarity calculations during prompt cache slot selection, offering developers greater insight into the process. The release supports a wide range of platforms, including macOS, Linux, Windows, and openEuler, though no new model architectures are introduced. This update enhances llama.cpp's utility for developers by improving transparency and platform compatibility.
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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.
