Auto Max on MMMU: score, rank and what it means
Auto Max scores 66.2 on MMMU, placing it #367 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.
Score distribution
The chart shows the top 10 models on MMMU, with Auto Max highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 3 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 4 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 5 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 6 | Grok 4 Pro | xAI | 1000000 | $19.00 | 85.4 |
| 7 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 8 | Claude Sonnet 4.5 Pro | Anthropic | 1000000 | $18.73 | 86.7 |
| 9 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 10 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
What this score means
On MMMU, Auto Max sits at #367 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 20.7 points. The median model in this index scores 70.0, which puts Auto Max below the midpoint.
OpenRouter models average 66.0 on this benchmark. Auto Max is 0.2 points above that provider line, so it is a stronger result than the average OpenRouter model.
Among mid-range models, the average is 65.0. Auto Max is 1.2 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 66.2 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 $8.41 per million input tokens, Auto Max is above the median input price of $4.00 across the 600 models scored on MMMU. 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 |
|---|---|---|---|---|
| GPT-4.1 Nano | OpenAI | 32768 | $7.42 | 70.5 |
| Mixtral Base | Mistral AI | 65536 | $2.95 | 71.1 |
| Mixtral Turbo Instruct | Together AI | 32768 | $3.16 | 71.9 |
| Auto Pro | OpenRouter | 8192 | $8.41 | 71.2 |
| Auto Max | OpenRouter | 8192 | $8.41 | 71.2 |
| Nemotron Nano Instruct | NVIDIA | 32768 | $2.33 | 67.4 |
| Arctic Chat | Snowflake | 16384 | $2.70 | 69.8 |
Other benchmarks for Auto Max
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 74.5 | 342 | 43th | |
| GPQA Diamond | 69.4 | 280 | 53th | |
| SWE-bench Verified | 58.7 | 345 | 43th | |
| HumanEval | 73.7 | 360 | 40th | |
| MATH-500 | 72.6 | 361 | 40th | |
| AIME 2025 | 68.5 | 287 | 52th | |
| LiveCodeBench | 60.0 | 368 | 39th | |
| IFEval | 78.1 | 366 | 39th | |
| TruthfulQA | 77.5 | 267 | 56th | |
| HellaSwag | 83.5 | 302 | 50th | |
| Arena Elo | 1365.1 | 331 | 45th |
FAQ
What score does Auto Max get on MMMU?
Auto Max scores 66.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Auto Max rank on MMMU?
It ranks #367 of 600 models, in the 39th percentile. The leader is GPT-5.2 Max at 86.9.
Is Auto Max good at MMMU?
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 MMMU score calculated?
MMMU is a multimodal 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 Max cost?
Auto Max costs $8.41 per million input tokens and $40.47 per million output tokens.