Who ranks #1 on the Mt Bench leaderboard?
As of August 31, 2026, Qwen2.5 72B Instruct by Qwen ranks #1 on Mt Bench at 93.5%. API pricing is $0.35/M input and $0.40/M output.
As of August 31, 2026, Qwen2.5 72B Instruct is #1 for Mt Bench at 93.5%. Ranked by the Mt Bench score 12 models in this index have a published Mt Bench score. Mt Bench leaderboard: rank models by Mt Bench next to live API token prices.
12 models. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price โ a dot under it is a worse deal than something on the line.
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As of August 31, 2026, Qwen2.5 72B Instruct by Qwen is #1 for Mt Bench at 93.5%. Ranked by the Mt Bench score This board also tracks Mt Bench. Next on the same board: Llama-3.3 Nemotron Super 49B v1 and DeepSeek-V2.5. This mt bench leaderboard ranks models by Mt Bench. Scores come from public evals. Prices are the live API rates in the table above.
Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); Anthropic Claude API pricing (https://platform.claude.com/docs/en/about-claude/pricing); Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing)
| Rank | Model | Mt Bench | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Qwen2.5 72B Instruct | 93.5% | $0.35 | $0.40 |
| 2 | Llama-3.3 Nemotron Super 49B v1 | 91.7% | $0.10 | $0.40 |
| 3 | DeepSeek-V2.5 | 90.2% | $0.14 | $0.28 |
| 4 | Hermes 3 70B | 89.9% | $0.35 | $1.40 |
| 5 | Qwen2.5 7B Instruct | 87.5% | $0.30 | $0.30 |
| 6 | Mistral Large 2 | 86.3% | $2.00 | $6.00 |
| 7 | Qwen2 7B Instruct | 84.1% | $0.30 | $0.30 |
| 8 | Mistral Small 3 24B Instruct | 83.5% | $0.07 | $0.14 |
Rank one eval at a time. All LLM benchmarks.
As of August 31, 2026, Qwen2.5 72B Instruct by Qwen ranks #1 on Mt Bench at 93.5%. API pricing is $0.35/M input and $0.40/M output.
The current Mt Bench ranking as of August 31, 2026 is 1. Qwen2.5 72B Instruct at 93.5%; 2. Llama-3.3 Nemotron Super 49B v1 at 91.7%; 3. DeepSeek-V2.5 at 90.2%.
Ministral 8B Instruct is the cheapest scored model on this mt bench leaderboard at $0.10/M input and $0.10/M output ($0.20 blended). Qwen2.5 72B Instruct still leads Mt Bench at 93.5%.
Not automatically. Qwen2.5 72B Instruct leads Mt Bench, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Mt Bench against input/output price, context window, and related evals.
Scores and API prices on this page are refreshed from published evals and provider rates. The snapshot is labeled August 31, 2026. Treat it as a current index, not a one-off blog post.
Mt Bench is a public LLM eval (the Mt Bench score). This page ranks models that have published a score, next to live API prices.
This page is the Mt Bench leaderboard. Models are sorted by Mt Bench, with input and output token prices on the same row so you can weigh score against cost. Official boards often omit price; that comparison is the point of this index.
Official eval pages own the methodology. This page keeps the published Mt Bench score next to live API $/M so you can pick a production SKU, not only a trophy number.