AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
Model reports
MMMU-Pro
Harder vision-required subset of MMMU. Input image ordering changes the result, so the protocol has to travel with the number.
Evaluation context and evidence
- Source
- Model reports
- Publisher
- Not recorded
- Benchmark release
- 2024-09-04
- Collected
- Not recorded
- Modality
- Not recorded
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 5
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Gemini 3.1 Pro | 80.5 | percent | Thinking (High), No tools | 2026-02-19 · document_publication | Gemini 3.1 Pro |
| Gemma 4 (31B) | 76.9 | percent | as reported | 2026-03-11 · document_publication | Gemma 4 (31B) |
| Kimi K3 | 83.4 | percent | reasoning=max, with Python | 2026-06-13 · document_publication | Kimi K3 |
| Kimi K3 | 81.6 | percent | reasoning=max, without tools | 2026-06-13 · document_publication | Kimi K3 |
| Qwen3.5-397B-A17B | 79.0 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |