MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark)
A benchmark of ~11.5K college-level multimodal questions spanning 30 subjects and 183 subfields across six disciplines, measuring a vision-language model's accuracy at jointly perceiving images (charts, diagrams, maps, tables, etc.) and reasoning with domain knowledge.
What this benchmark measures
A benchmark of ~11.5K college-level multimodal questions spanning 30 subjects and 183 subfields across six disciplines, measuring a vision-language model's accuracy at jointly perceiving images (charts, diagrams, maps, tables, etc.) and reasoning with domain knowledge.
Rows on this page are sourced from public benchmark artifacts, leaderboard exports, or source-linked model reports. Each row keeps benchmark version, source model name, and available run details attached to the score.
The metric shown here is accuracy. It should be interpreted within MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark), not compared as part of a site-wide ranking.