OCR-MetaReasoning - Document Logic: leaderboard

OCR-MetaReasoning answer score on the document logic OCR-object category of its text-rich image questions (arXiv 2608.30678v1, Table 2). 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: Estimated already saturated. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview) (Thinking)93#64 (Gemini 3.1 Pro (Preview))
2GPT-5.4 (Medium)90.8#83 (GPT-5.4)
3Claude Sonnet 4.6 (Thinking)88.1#94 (Claude Sonnet 4.6)
4GPT-5.4 Mini (Medium)87.8#228 (GPT-5.4 Mini)
5Qwen 3 VL 235B A22B (Thinking)86.3#236
6GPT-5.4 (Non-reasoning)85#83 (GPT-5.4)
7Qwen 3 VL 235B A22B Instruct78.8#280
8Qwen 3 VL 30B A3B (Thinking)78.6#348
9GLM-4.6V (Reasoning)78.1#330 (GLM-4.6V)
10Kimi K2.5 (Non-reasoning)77.5#152 (Kimi K2.5)
11Qwen 3 VL 8B (Thinking)76.8#423
12Grok 4.20 (Non-reasoning)76.6#179 (Grok 4.20)
13GPT-5.4 Mini (Non-reasoning)75.1#228 (GPT-5.4 Mini)
14Qwen 3 VL 30B A3B Instruct66.6#390
15Qwen 3 VL 8B Instruct65.5#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-document-logic · How It Works · Data refreshed daily, snapshot 2026-11-05.