HELM VHELM - Mmmu - Manage: leaderboard

VHELM (Stanford CRFM HELM for vision-language models, run v2.1.2) MMMU Manage: college-level multiple-choice questions over images from the MMMU validation set for this subject; 24 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 2.5 Pro (Preview 03-25)83.33#126
2Claude 3.5 Sonnet (20240620)79.17#308
3O4 Mini (2025-04-16)79.17#183
4O1 (2024-12-17)79.17#157
5Claude 3.5 Sonnet (20241022)75#302
6GPT-4.1 (2025-04-14)70.83#257
7O3 (2025-04-16)70.83#125
8Gemini 2.0 Pro (Preview 02-05)70.83#318
9GPT-4.1 Mini66.67#363
10Gemini 2.0 Flash (Preview)66.67#376
11Claude 3 Opus (20240229)66.67#428
12Llama 4 Maverick Instruct FP862.5#424
13GPT-4.562.5#278
14Gemini 2.0 Flash58.33#351
15Llama 4 Scout Instruct58.33#547

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