Auto Nano on MMLU-Pro: score, rank and what it means
Auto Nano scores 65.0 on MMLU-Pro, placing it #453 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with Auto Nano highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, Auto Nano sits at #453 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 26.6 points. The median model in this index scores 76.1, which puts Auto Nano below the midpoint.
OpenRouter models average 72.7 on this benchmark. Auto Nano is 7.7 points below that provider line, so it is a weaker result than the average OpenRouter model.
Among mid-range models, the average is 71.5. Auto Nano is 6.5 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 65.0 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $2.83 per million input tokens, Auto Nano is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Yi-Lightning 8B | 01.AI | 4096 | $1.16 | 59.2 |
| GPT-NeoX Base | EleutherAI | 16384 | $1.22 | 59.7 |
| Llama 4 Maverick 7B | Meta AI | 4096 | $1.52 | 61.9 |
| GLM-4.5 7B | Zhipu AI | 8192 | $1.32 | 60.2 |
| Auto Nano | OpenRouter | 4096 | $2.83 | 57.1 |
| Llama 3 DeepInfra 8B | DeepInfra | 8192 | $1.05 | 57.4 |
| QwQ 7B | Alibaba Cloud | 8192 | $1.11 | 58.1 |
Other benchmarks for Auto Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 50.2 | 520 | 13th | |
| SWE-bench Verified | 44.2 | 475 | 21th | |
| HumanEval | 62.7 | 461 | 23th | |
| MATH-500 | 60.0 | 464 | 23th | |
| AIME 2025 | 44.2 | 505 | 16th | |
| LiveCodeBench | 46.5 | 483 | 20th | |
| IFEval | 66.5 | 508 | 15th | |
| TruthfulQA | 61.7 | 509 | 15th | |
| HellaSwag | 72.2 | 490 | 18th | |
| MMMU | 55.2 | 494 | 18th | |
| Arena Elo | 1256.0 | 481 | 20th |
FAQ
What score does Auto Nano get on MMLU-Pro?
Auto Nano scores 65.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Auto Nano rank on MMLU-Pro?
It ranks #453 of 600 models, in the 25th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Auto Nano good at MMLU-Pro?
It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.
How is the MMLU-Pro score calculated?
MMLU-Pro is a knowledge benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Auto Nano cost?
Auto Nano costs $2.83 per million input tokens and $14.41 per million output tokens.