OCR-MetaReasoning - Meta-Deductive: leaderboard

OCR-MetaReasoning answer score on deductive meta-reasoning items over text-rich images (arXiv 2608.30678v1, Table 2); MRMS averages the three reasoning types. Percentage (100 times the normalized score), higher is better; reasoning modes follow the paper's Table 24.

Metric: Answer Score (%). Source: arxiv.org. Saturation forecast: Around February 2027. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview) (Thinking)80.7#64 (Gemini 3.1 Pro (Preview))
2GPT-5.4 (Medium)80.6#83 (GPT-5.4)
3GPT-5.4 (Non-reasoning)77.9#83 (GPT-5.4)
4GPT-5.4 Mini (Medium)77.7#228 (GPT-5.4 Mini)
5Claude Sonnet 4.6 (Thinking)77.5#94 (Claude Sonnet 4.6)
6Qwen 3 VL 235B A22B (Thinking)74.8#236
7Qwen 3 VL 235B A22B Instruct72.5#280
8GLM-4.6V (Reasoning)72#330 (GLM-4.6V)
9Kimi K2.5 (Non-reasoning)71.8#152 (Kimi K2.5)
10GPT-5.4 Mini (Non-reasoning)70.7#228 (GPT-5.4 Mini)
11Qwen 3 VL 8B (Thinking)70.3#423
12Grok 4.20 (Non-reasoning)70.3#179 (Grok 4.20)
13Qwen 3 VL 30B A3B (Thinking)69.1#348
14Qwen 3 VL 30B A3B Instruct64#390
15Qwen 3 VL 8B Instruct59.1#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-meta-deductive · How It Works · Data refreshed daily, snapshot 2026-11-05.