MMPCBench - Expression Error 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 whose premise description is too vague or whose task intent is unclear; 0-100, higher is better.

Metric: PCQ (0-100). Source: arxiv.org. Saturation forecast: Around 2032. 14 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 VL 235B A22B Instruct30.7#280
2Qwen 3 VL 30B A3B Instruct24.8#390
3Qwen 3 VL 8B Instruct21.3#419
4GPT-5.215.3#115
5GPT-5.1 (High)14.4#145 (GPT-5.1)
6Claude Sonnet 4.5 (Thinking)13.8#148 (Claude Sonnet 4.5)
7Gemini 3 Pro13.6#82
8GPT-5 Mini12.9#193
9Gemini 3 Flash10.4#103
10Gemma 3 12B (IT)6.4#672
11Gemma 3 27B (IT)5.8#528
12Gemma 3 4B (IT)5.1#997
13GLM-4.6V2.6#330

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

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