OCR-MetaReasoning: leaderboard

OCR-MetaReasoning tests meta-reasoning by multimodal models on text-rich images (arXiv 2608.30678v1). MRMS, the Meta-Reasoning Macro Score, is the macro average over deductive, inductive and abductive items as a percentage, higher is better, from the paper's Table 2; reasoning modes follow the paper's Table 24.

Metric: Meta-Reasoning Macro Score (%). Source: arxiv.org. Saturation forecast: Around February 2027. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview) (Thinking)89.3#64 (Gemini 3.1 Pro (Preview))
2GPT-5.4 (Medium)87.7#83 (GPT-5.4)
3Claude Sonnet 4.6 (Thinking)84.3#94 (Claude Sonnet 4.6)
4GPT-5.4 Mini (Medium)84#228 (GPT-5.4 Mini)
5GPT-5.4 (Non-reasoning)83#83 (GPT-5.4)
6Qwen 3 VL 235B A22B (Thinking)81.5#236
7Kimi K2.5 (Non-reasoning)79.6#152 (Kimi K2.5)
8Qwen 3 VL 235B A22B Instruct77#280
9GLM-4.6V (Reasoning)75.9#330 (GLM-4.6V)
10Grok 4.20 (Non-reasoning)75.2#179 (Grok 4.20)
11Qwen 3 VL 30B A3B (Thinking)74.7#348
12Qwen 3 VL 8B (Thinking)74.5#423
13GPT-5.4 Mini (Non-reasoning)72#228 (GPT-5.4 Mini)
14Qwen 3 VL 30B A3B Instruct65#390
15Qwen 3 VL 8B Instruct59#419

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

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