Daily By Model High Reasoning Models (excluding free models) TOP 10

Thinking Ratio Indicator Guide

The thinking ratio is calculated based on the reasoning tokens / input tokens ratio. The higher this ratio, the more internal reasoning processes the model undergoes.

This metric indicates how deeply the model thinks before generating a response. Models with a higher thinking ratio are likely to produce more sophisticated results in tasks such as complex problem solving, logical reasoning, and multi-step planning. However, a high thinking ratio does not necessarily mean better performance. In some tasks, excessive internal reasoning may incur unnecessary computational costs or be inefficient in situations where concise responses are needed. Therefore, this metric should be interpreted according to the characteristics and purpose of the task.

Rank Model Name Input Tokens Reasoning Tokens Thinking Ratio
1 perplexity/sonar-deep-research 3.84M 121.62M 31.6874
2 minimax/minimax-m1 30.63M 83.50M 2.7261
3 qwen/qwen3-8b-04-28 36.44M 38.80M 1.0645
4 openai/o1-mini 19.46M 15.49M 0.796
5 deepseek/deepseek-r1-distill-qwen-1.5b 2.54M 2.00M 0.7858
6 deepseek/deepseek-r1-0528-qwen3-8b 162.52M 111.22M 0.6843
7 thudm/glm-z1-32b-0414 50.18K 28.99K 0.5778
8 thudm/glm-4.1v-9b-thinking 7.61M 4.11M 0.5405
9 openai/o1-mini-2024-09-12 1.33M 634.96K 0.4767
10 z-ai/glm-4.5-air 429.77M 199.26M 0.4636