GLM 4.7 Flash Q6: A Hands-On Experience

A user has shared their experience using the GLM 4.7 Flash Q6 model for refactoring tasks in personal web projects. The focus was on handling Roo code, where the model demonstrated a remarkable ability to avoid code fragmentation.

Performance and Comparison with Other Models

Specifically, for agentic tools, GLM 4.7 Flash Q6 proved more reliable and precise than GPT-OSS 120b, GLM 4.5 Air, and Devstral 24b. The user specified the parameters used with llama.cpp to leverage UD-Q6_K_XL with 48k context tokens on an RTX 5090, achieving approximately 150 tok/s.

Configuration Details

The configuration used included the llama-server command with specific parameters for the model, port, host, activation of -fa, context size, temperature, and other parameters for inference.