xMMMU
Vision language models answer college-level MMMU questions translated into 7 languages. Scored by accuracy.
Released as part of PangeaBench with the Pangea model.
Made by Carnegie Mellon University (PangeaBench) Released Oct 2024 General visual questions All tasks public Last in a system card May 2025
Last model added May 2025
- Level
- University Undergraduates and entry-level professionals
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Multiple choice
1
Model scored in lab cards
1
System card reports it, from 1 lab
Aya Vision 32B leads with 45.1%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1
Aya Vision 32B 45.1%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 45.1% | May 2025 | Model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Reported by the lab in its model card
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 13 May 2025 | | 45.1 | xMMMU, Aya Vision languages (Table 4) | Capabilities |
More in Vision
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- MATH-Vision (MathVision) In use 3,040 competition math problems with visual context. Answer accuracy.
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- ChartQA In use Models answer human-written and generated questions about chart images that need visual and arithmetic reasoning. Scored by relaxed accuracy with a 5 percent numeric tolerance.
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- DocVQA In use Models answer 50,000 questions about 12,000 scanned document images by reading their text and layout. Scoring is ANLS, a string similarity to reference answers.
Seed1.5-VL 96.9%