OmniHandwritingOCR - English Text: leaderboard
A subset of OmniHandwritingOCR (East China Normal University, 2026): 11,859 English handwritten text images from GNHK and IAM lines, filtered toward samples a strong reference model found hard. Systems transcribe each image to Markdown zero-shot, scored by 1-NED, one minus the normalized edit distance to the ground truth, in percent; higher is better.
Metric: 1-NED (%; one minus the normalized Levenshtein distance between the transcription and the ground truth, averaged over 11,859 English handwritten text images (GNHK, IAM lines); zero-shot Markdown transcription from one image with one task-neutral instruction for every system; task-specific normalization and tokenization, no semantic correction). Source: arxiv.org. Saturation forecast: Estimated already saturated. 13 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-4o | 81.29 | #741 |
| 2 | InternVL3-78B | 81.14 | #738 |
| 3 | Gemma 3 27B (IT) | 74.86 | #1289 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=omnihandwritingocr-english-text · How It Works · Data refreshed daily, snapshot 2026-11-13.