Monthly 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 70.54M 2.2B 30.7959
2 deepseek/deepseek-r1-distill-qwen-1.5b 104.33M 132.39M 1.2689
3 deepseek/deepseek-r1-distill-qwen-7b 127.39M 109.51M 0.8596
4 microsoft/mai-ds-r1 37.40M 31.96M 0.8546
5 thudm/glm-z1-rumination-32b-0414 238.59K 202.33K 0.848
6 x-ai/grok-3-mini-beta 23.2B 16.7B 0.7194
7 openai/o1-preview 19.59M 13.92M 0.7106
8 deepseek/deepseek-r1-distill-llama-70b 17.5B 12.3B 0.7027
9 qwen/qwen3-8b-04-28 3.0B 2.0B 0.6581
10 openai/o3-mini-high-2025-01-31 442.10M 284.41M 0.6433