DatBench - Document Understanding: leaderboard

DatBench (DatologyAI, 2026) document-understanding suite: reading and extracting key information from scanned or digital documents, forms and receipts, drawn from CC-OCR document parsing and extraction, OCR-VQA, OCRBench-V2 and DocVQA after DatBench's curation (multiple-choice items turned into free-form answers judged by Qwen3-30B or scored circularly, items solvable without the image or flagged by a GPT-5.2 judge as mislabeled removed, and a high-discrimination subset kept). Accuracy in percent, higher is better, with generation capped at 4,096 tokens; the curation used the responses of the same 1B-10B models the paper scores.

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Around February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 VL 4B Instruct71#1281
2Qwen2.5-Omni-7B70.1#1797
3Qwen 2.5 VL 7B Instruct62.8#1842
4Qwen 3 VL 8B Instruct57.2#982
5Qwen 3 VL 8B (Thinking)27#887
6GLM-4.1V-9B (Thinking)26.5#1061 (GLM-4.1V-9B)
7Qwen 3 VL 4B (Thinking)24.7#1303
8InternVL2-8B18.3#3025
9InternVL2.5-2B15.9#6868
10Gemma 3 4B (IT)9.2#3848

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=datbench-document-understanding · How It Works · Data refreshed daily, snapshot 2026-11-12.