Benchmark Almanac

xMMMU

Aya Vision 32B 45.1% Only in system cards

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. 1 Aya Vision 32B 45.1%
#ModelScoreSettingDateSource
1 Aya Vision 32B 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
0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) Aya Vision 32B 0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) Aya Vision 32B

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.

DateDocumentScoreAs the document writes itSection
13 May 2025 Aya Vision 32B technical report 45.1 xMMMU, Aya Vision languages (Table 4) Capabilities

More in Vision

All 234 in Vision
  • MMMU In use 11.5K college-level multimodal questions across 30 subjects. Multiple-choice and open accuracy. GPT-5.1 85.4%
  • MMMU-Pro In use Harder MMMU: college-level multimodal questions with more options and vision-only inputs to remove text shortcuts. Kimi K3.1 Pro 84.1%
  • CharXiv In use Chart understanding on real arXiv figures. Reasoning questions require synthesizing information from complex charts. Claude Fable 5 93.5%
  • MATH-Vision (MathVision) In use 3,040 competition math problems with visual context. Answer accuracy. Qwen 3.8 Max 97.7%
  • 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. Command A Vision 90.9%
  • 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%