Strix Halo and MiniMax Q3 K_XL: A Winning Combination?

A recent test on Strix Halo, equipped with 128GB of RAM (Bosgame M5) and the Ubuntu 25.10 operating system, highlighted surprising performance in running the MiniMax Q3 K_XL model. The user reported a speed of approximately 30 tokens per second in TG mode.

Practical Implications

This speed makes MiniMax Q3 K_XL particularly suitable for activities that require coherence and in-depth knowledge, such as brainstorming and discussing general topics. While not reaching the speed of gpt-oss-120b, especially in PP mode, MiniMax Q3 stands out for its ability to provide relevant and useful answers in various contexts. The user suggests considering it a valuable complement to other large language models (LLMs) such as gpt-oss-120b and GLM-4.5-AIR.

The Landscape of LLM Models

The development and refinement of LLM models are constantly evolving. The technicians are constantly working to improve performance, reduce computing costs, and expand areas of application. The integration of different models, each with its own strengths, allows to tackle a wide range of tasks more efficiently and effectively.