HELM VHELM - Mmmu - Design: leaderboard

VHELM (Stanford CRFM HELM for vision-language models, run v2.1.2) MMMU Design: 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
2Gemini 1.5 Flash (002)90#587
3O3 (2025-04-16)90#125
4GPT-4.1 Mini86.67#363
5Claude 3.5 Sonnet (20241022)86.67#302
6O4 Mini (2025-04-16)86.67#183
7O1 (2024-12-17)86.67#157
8Claude 3.5 Sonnet (20240620)83.33#308
9Gemini 2.5 Pro (Preview 03-25)83.33#126
10GPT-4.1 (2025-04-14)83.33#257
11GPT-4o (2024-08-06)83.33#343
12GPT-4o (2024-05-13)83.33#337
13GPT-4o (2024-11-20)83.33#392
14Gemini 2.0 Flash (Preview)83.33#376
15Claude 3 Haiku (20240307)83.33#780

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-design · How It Works · Data refreshed daily, snapshot 2026-11-05.