MMPCBench - Missing Premise PCQ: leaderboard

MMPCBench (arXiv 2608.29286v1, Table 2): proactive critique of flawed multimodal inputs for 14 MLLMs; a judge panel of GPT-5.2, Gemini-3-Pro and Claude-Sonnet-4 scores the responses, and two of those judges are also evaluated. PCQ on inputs with partly occluded visual premises, a missing image or instruction, or an image unrelated to the question; 0-100, higher is better.

Metric: PCQ (0-100). Source: arxiv.org. Saturation forecast: Around 2030. 14 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.5 (Thinking)44.6#148 (Claude Sonnet 4.5)
2Qwen 3 VL 235B A22B Instruct42.2#280
3Qwen 3 VL 30B A3B Instruct38.3#390
4GPT-5.1 (High)37.6#145 (GPT-5.1)
5Qwen 3 VL 8B Instruct36.8#419
6GPT-5 Mini28.1#193
7GPT-5.225.8#115
8Gemini 3 Pro24.9#82
9Gemma 3 12B (IT)21#672
10Gemma 3 27B (IT)20.6#528
11Gemini 3 Flash19.9#103
12GLM-4.6V11.9#330
13Gemma 3 4B (IT)11.8#997

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=mmpcbench-missing-premise-pcq · How It Works · Data refreshed daily, snapshot 2026-11-05.