HELM VHELM - Mmmu - Energy and Power: leaderboard

VHELM (Stanford CRFM HELM for vision-language models, run v2.1.2) MMMU Energy and Power: 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)80#183
2O3 (2025-04-16)80#125
3O1 (2024-12-17)73.33#157
4Claude 3 Opus (20240229)60#428
5Gemini 1.5 Pro (002)56.67#368
6Llama 4 Maverick Instruct FP856.67#424
7Gemini 2.0 Pro (Preview 02-05)53.33#318
8Gemini 1.5 Flash (002)50#587
9Claude 3.5 Sonnet (20240620)50#308
10GPT-4 Turbo50#417
11Gemini 2.0 Flash (Preview)50#376
12Gemini 2.5 Pro (Preview 03-25)46.67#126
13Claude 3 Sonnet (20240229)46.67#694
14GPT-4.1 Mini43.33#363
15GPT-4.543.33#278

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-energy-and-power · How It Works · Data refreshed daily, snapshot 2026-11-05.