Reasoning models, ranked
A reasoning model thinks in tokens before it answers, and those tokens are output tokens on your bill. The quality gain on multi-step problems is real, and so is the multiplier: we reserve roughly three times the usual output when a request goes to one of these, then charge only what the model actually used.
Most used in this category
Each model's share of this category's usage over the last 30 days, and its output price per 1M tokens in toman.
- 1
Gemini 3.8 Flash50% share1,298,323 toman - 2Gemini 2.5 Flash Lite29% share138,488 toman
- 3Gemini 3.1 Flash Lite5.6% share519,329 toman
- 4Claude Sonnet 54.7% share3,462,194 toman
- 5Gemini 2.5 Flash4.1% share865,548 toman
Best value in this category
Score out of 100: 50% cheapness, 30% capabilities, 20% context size — not a quality benchmark.
| # | Model | Context (tokens) | ≈ 1,000 words (toman) | Score |
|---|---|---|---|---|
| 1 | 1GLM Flash Latest | 1,048,576 | 54 | 87.7 |
| 2 | 2Qwen3.7 Flash | 1,000,000 | 72 | 84.4 |
| 3 | 3GPT-6 Luna Pro (batch) | 1,050,000 | 135 | 83.8 |
| 4 | 4GPT-6 Luna (batch) | 1,050,000 | 135 | 83.8 |
| 5 | 5GPT-5 Nano (batch) | 400,000 | 101 | 83.6 |
| 6 | 6Claude Haiku 5.5 (batch) | 1,000,000 | 135 | 83.6 |
| 7 | 7Ling 3.0 Tiny | 262,144 | 27 | 82.4 |
| 8 | 8Ling 3.0 Flash | 262,144 | 38 | 80.7 |
| 9 | 9Gemma 4 26B A4B | 262,144 | 67 | 80.6 |
| 10 | 10GLM 5.3 Flash (batch) | 1,048,576 | 104 | 80.6 |
| 11 | 11Gemini 2.5 Flash Lite | 1,048,576 | 225 | 78.2 |
| 12 | 12Ternary Bonsai 2 9B | 262,144 | 95 | 76.8 |
| 13 | 13Qwen3.5-Flash | 1,000,000 | 146 | 76.8 |
| 14 | 14Nex-N2.5-Mini | 262,144 | 56 | 76.5 |
| 15 | 15GPT-6 Luna | 1,050,000 | 270 | 76.3 |
Full list of reasoning models, and what they cost with prices →