MMErroR - Error Presence Detection - Mathematics & Logic: leaderboard

MMErroR (Shi et al., ACL 2026) error presence detection on its Mathematics & Logic samples: the model must flag an image-grounded reasoning chain as erroneous and name the correct type of its single injected error. Accuracy (%); higher is better.

Metric: Error Presence Detection Accuracy (%). Source: arxiv.org. Saturation forecast: Around February 2027. 12 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro (Preview)61.86#111
2GPT-5.2 (xHigh)60.96#172 (GPT-5.2)
3Qwen 3 VL 32B (Thinking)57.06#557
4Kimi K2.556.46#252
5Seed 2.0 Pro56.16#209
6Claude Opus 4.555.26#152
7Grok 451.65#306
8Qwen 3 VL 32B Instruct40.84#582
9Qwen-VL-Max39.04#1226
10GLM-4.6V27.93#698
11Llama 4 Scout Instruct24.62#1532
12Llama 4 Maverick Instruct23.12#1125

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=mmerror-error-presence-detection-mathematics-logic · How It Works · Data refreshed daily, snapshot 2026-11-12.