MT-Bench
MT-Bench is a challenging multi-turn benchmark that measures the ability of large language models to engage in coherent, informative, and engaging conversations. It uses strong LLMs as judges for scalable and explainable evaluation of multi-turn dialogue capabilities.
Hermes 3 70B from Nous Research currently leads the MT-Bench leaderboard with a score of 8.990 across 12 evaluated AI models.
Hermes 3 70B leads with 9.0%, followed by 
Qwen2.5 72B Instruct at 0.9% and 
Llama-3.3 Nemotron Super 49B v1 at 0.9%.
Progress Over Time
Interactive timeline showing model performance evolution on MT-Bench
MT-Bench Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Nous Research | 70B | — | — | ||
| 2 |  Alibaba Cloud / Qwen Team | 73B | — | — | ||
| 3 | 50B | — | — | |||
| 4 |  DeepSeek | 236B | — | — | ||
| 5 | Alibaba Cloud / Qwen Team | 8B | — | — | ||
| 6 |  Mistral AI | 123B | — | — | ||
| 7 | Alibaba Cloud / Qwen Team | 8B | — | — | ||
| 8 | Mistral AI | 24B | — | — | ||
| 9 | Mistral AI | 8B | — | — | ||
| 10 | 8B | — | — | |||
| 11 | Mistral AI | 12B | — | — | ||
| 12 | 70B | — | — |
FAQ
Common questions about MT-Bench.
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