MMOOC - Visual False Premises (Multiple Choice): leaderboard

MMOOC tests whether multimodal models decline questions their image and context cannot answer, and explain why. This board covers multiple-choice questions where the question asserts something the image contradicts, and averages the share of correct refusals with a judge rating of the abstention reasoning.

Metric: Out-of-context score (%; mean of the refusal rate, the share of the Visual False Premises Multiple Choice questions, which the image and context cannot answer, that the model correctly declines, and refusal rationality, the mean 0-1 judge score of its abstention reasoning in steps of 0.25; judge scores averaged over GPT-5.6, Claude Opus 5 and DeepSeek-V4-Pro). Source: arxiv.org. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemma 4 31B34.25#394
2Qwen 3.5 122B A10B32.25#331
3Ministral 3 8B31.25#2023
4Gemma 4 26B28.5#612
5Qwen 3.5 27B27.5#359
6Llama 4 Maverick26.25#1099
7GPT-4o24.75#741
8Ministral 3 14B24.5#1845
9O122.75#393
10O322.25#228
11Gemini 3.1 Pro (Preview)14.25#94
12Claude Opus 4.65.25#102
13InternVL3-8B5#1688

Interactive version: theaggregate.ai/benchmark?slug=mmooc-visual-false-premises-multiple-choice · How It Works · Data refreshed daily, snapshot 2026-11-13.