Gemini 2.5 Pro Nano on MMMU: score, rank and what it means
Gemini 2.5 Pro Nano scores 65.9 on MMMU, placing it #374 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 Gemini 2.5 Pro Nano 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, Gemini 2.5 Pro Nano sits at #374 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 21.0 points. The median model in this index scores 70.0, which puts Gemini 2.5 Pro Nano below the midpoint.
Google DeepMind models average 74.9 on this benchmark. Gemini 2.5 Pro Nano is 9.0 points below that provider line, so it is a weaker result than the average Google DeepMind model.
Among mid-range models, the average is 65.0. Gemini 2.5 Pro Nano is 0.9 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 65.9 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 $7.28 per million input tokens, Gemini 2.5 Pro Nano 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 |
|---|---|---|---|---|
| Embed 4 Max | Cohere | 8192 | $5.68 | 66.1 |
| Firefunction Turbo | Fireworks AI | 32768 | $8.44 | 70.7 |
| ERNIE 4.0 Mini | Baidu | 32768 | $7.11 | 68.8 |
| Llama 3 Replicate Base | Replicate | 65536 | $3.15 | 72.1 |
| Gemini 2.5 Pro Nano | Google DeepMind | 32768 | $7.28 | 69.2 |
| Molmo Instruct | Allen Institute for AI | 32768 | $2.53 | 68.3 |
| Claude 3.7 Sonnet Nano | Anthropic | 65536 | $6.93 | 68.9 |
Other benchmarks for Gemini 2.5 Pro Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 71.4 | 385 | 36th | |
| GPQA Diamond | 65.4 | 353 | 41th | |
| SWE-bench Verified | 54.3 | 390 | 35th | |
| HumanEval | 71.1 | 387 | 36th | |
| MATH-500 | 74.9 | 327 | 46th | |
| AIME 2025 | 63.7 | 360 | 40th | |
| LiveCodeBench | 59.2 | 376 | 37th | |
| IFEval | 79.9 | 334 | 44th | |
| TruthfulQA | 74.4 | 343 | 43th | |
| HellaSwag | 80.7 | 375 | 38th | |
| Arena Elo | 1349.7 | 364 | 39th |
FAQ
What score does Gemini 2.5 Pro Nano get on MMMU?
Gemini 2.5 Pro Nano scores 65.9 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Gemini 2.5 Pro Nano rank on MMMU?
It ranks #374 of 600 models, in the 38th percentile. The leader is GPT-5.2 Max at 86.9.
Is Gemini 2.5 Pro Nano 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 Gemini 2.5 Pro Nano cost?
Gemini 2.5 Pro Nano costs $7.28 per million input tokens and $28.44 per million output tokens.