HELM VHELM - Mmmu - Literature: leaderboard

VHELM (Stanford CRFM HELM for vision-language models, run v2.1.2) MMMU Literature: college-level multiple-choice questions over images from the MMMU validation set for this subject; 30 questions, prefix quasi-exact match. Percent correct, 0-100, higher is better; a small sample.

Metric: Prefix Quasi-Exact Match (%). Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 48 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 1.5 Pro (002)90#368
2GPT-4.1 Mini86.67#363
3Claude 3.5 Sonnet (20241022)86.67#302
4GPT-4.1 Nano86.67#730
5Gemini 2.0 Flash86.67#351
6Gemini 1.5 Flash (002)86.67#587
7Claude 3.5 Sonnet (20240620)86.67#308
8GPT-4o Mini (2024-07-18)86.67#568
9Gemini 2.5 Pro (Preview 03-25)86.67#126
10GPT-4.1 (2025-04-14)86.67#257
11GPT-4o (2024-05-13)86.67#337
12GPT-4 Turbo86.67#417
13O4 Mini (2025-04-16)86.67#183
14O3 (2025-04-16)86.67#125
15GPT-4o (2024-11-20)86.67#392

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=helm-vhelm-mmmu-literature · How It Works · Data refreshed daily, snapshot 2026-11-05.