HELM VHELM - Mmmu - Public Health: leaderboard

VHELM (Stanford CRFM HELM for vision-language models, run v2.1.2) MMMU Public Health: 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
1O4 Mini (2025-04-16)100#183
2Gemini 2.5 Pro (Preview 03-25)96.67#126
3O3 (2025-04-16)96.67#125
4O1 (2024-12-17)96.67#157
5Gemini 1.5 Pro (002)90#368
6Claude 3.5 Sonnet (20240620)90#308
7GPT-4.586.67#278
8Llama 4 Maverick Instruct FP883.33#424
9Gemini 2.0 Pro (Preview 02-05)83.33#318
10GPT-4.1 Mini80#363
11Gemini 2.0 Flash80#351
12Claude 3.5 Sonnet (20241022)76.67#302
13GPT-4o (2024-08-06)76.67#343
14GPT-4 Turbo76.67#417
15Gemini 2.0 Flash (Preview)76.67#376

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