GLM-4.7-Flash stands out for its structured and well-defined thinking process, according to a user who thoroughly tested it. ## Analysis of the Thinking Process The model analyzes requests in depth, breaking down the process into several phases: 1. Request analysis 2. Brainstorming 3. Response drafting 4. Response refinement (with multiple options) 5. Revision 6. Optimization 7. Final response This approach, although slower than other models like Nemotron-nano, produces higher quality results. The user plans to use GLM-4.7-Flash for data analysis tasks, once the fine-tuning is finalized. ## Configuration and Performance The user encountered stability issues with the default configuration on an M4 Macbook Air, resolved by modifying the temperature, repeat penalty, and top-p parameters. Despite this, the token processing speed is lower compared to other models. Large language models (LLMs) continue to evolve, offering increasingly sophisticated capabilities. A model's ability to simulate a structured thought process represents a significant step towards greater transparency and controllability of deliveries.