Auto Max on MMLU-Pro: score, rank and what it means
Auto Max scores 74.5 on MMLU-Pro, placing it #342 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 Max 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 Max sits at #342 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 17.1 points. The median model in this index scores 76.1, which puts Auto Max below the midpoint.
OpenRouter models average 72.7 on this benchmark. Auto Max is 1.8 points above that provider line, so it is a stronger result than the average OpenRouter model.
Among mid-range models, the average is 71.5. Auto Max is 3.0 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 74.5 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 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 |
|---|---|---|---|---|
| Phi-3.5 Instruct | Microsoft | 16384 | $2.67 | 70.1 |
| o4 Nano | OpenAI | 65536 | $8.61 | 72.0 |
| Llama 3 Anyscale Base | Anyscale | 65536 | $3.23 | 72.9 |
| Molmo Instruct | Allen Institute for AI | 32768 | $2.53 | 68.3 |
| Auto Max | OpenRouter | 8192 | $8.41 | 71.2 |
| DBRX Base | Databricks | 32768 | $2.63 | 69.1 |
| Llama 3 Novita Base | Novita AI | 8192 | $3.06 | 70.3 |
Other benchmarks for Auto Max
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| 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 | |
| MMMU | 66.2 | 367 | 39th | |
| Arena Elo | 1365.1 | 331 | 45th |
FAQ
What score does Auto Max get on MMLU-Pro?
Auto Max scores 74.5 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Auto Max rank on MMLU-Pro?
It ranks #342 of 600 models, in the 43rd percentile. The leader is GPT-5.2 Pro at 91.6.
Is Auto Max 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 Max cost?
Auto Max costs $8.41 per million input tokens and $40.47 per million output tokens.