Benchmark
MMMU-Pro
vision
multimodal
reasoning
general
multimodal
A more robust multi-discipline multimodal understanding benchmark that enhances MMMU through a three-step process: filtering text-only answerable questions, augmenting candidate options, and introducing vision-only input settings. Achieves significantly lower model performance (16.8-26.9%) compared to original MMMU, providing more rigorous evaluation that closely mimics real-world scenarios.
Top 10
榜单概览
数据说明
分数为 0-100 百分制综合成绩（Elo 榜为相对评分，仅供同榜内比较）。评测分数属事实数据，整理自公开评测体系与厂商公开资料，部分分数为厂商自报口径，不同榜单的评测方法与数据集可能存在差异，请结合多个榜单交叉参考。
Ranking
模型排名
| 名次 | 模型 | 机构 | 分数 | 来源 |
|---|---|---|---|---|
| 1 | Gemini 3.5 Flash | 83.6 | 来源 | |
| 2 | GPT-5.6 Sol | OpenAI | 83.0 | 来源 |
| 3 | GPT-5.5 | OpenAI | 81.2 | 来源 |
| 4 | GPT-5.4 | OpenAI | 81.2 | 来源 |
| 5 | GPT-5.6 Terra | OpenAI | 80.7 | 来源 |
| 6 | Gemini 3.1 Pro Preview | 80.5 | 来源 | |
| 7 | GPT-5.6 Luna | OpenAI | 78.4 | 来源 |
| 8 | GPT-5 | OpenAI | 78.4 | 来源 |