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.