VeriOCRBench - Contextual Dimension (Assisted): leaderboard

The contextual verification dimension of VeriOCRBench (Zhou et al., 2026): 400 OCR-grounded tasks with the traps domain mismatch and hallucinatory target, where the provided context imposes a wrong domain on the image or refers to a target that does not exist in it. Diagnosis accuracy is the percentage on which the model both rejects the task and names the correct trap mechanism, judged by GPT-4o; higher is better. Assisted setting: the prompt tells the model to check that the task is completable before answering.

Metric: Diagnosis accuracy (%; the 400 trap-injected tasks of the contextual verification dimension (domain mismatch and hallucinatory target: the provided context imposes a wrong domain on the image or refers to a target that does not exist in it); the model must reject the task and name the ground-truth trap mechanism; judged by GPT-4o at temperature 0; assisted paradigm: a meta-instruction asks the model to verify the task first). Source: arxiv.org. Saturation forecast: Estimated already saturated. 15 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 397B A17B96.5#242
2GPT-596#163
3Claude Sonnet 4.595.75#244
4Qwen 3.5 35B A3B95.5#480
5Qwen 3.5 122B A10B93.5#329
6GPT-4o93.25#741
7InternVL3-38B91.5#905
8Llama 4 Maverick75.75#1105
9Llama 4 Scout75.5#1787
10Gemini 3.1 Pro (Preview)4.5#91

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

Interactive version: theaggregate.ai/benchmark?slug=veriocrbench-contextual-dimension-assisted · How It Works · Data refreshed daily, snapshot 2026-11-12.