Comprehensive benchmarks covering multiple aspects of OCR performance.
Tests 8 core OCR capabilities across 23 tasks. Evaluates LMMs on text recognition, referring, extraction.
Leading models on OCRBench v2.
| # | Model | overall-zh-private | Year | Source |
|---|---|---|---|---|
| ★ | Gemini 2.5 Pro | 62.2 | 2025 | paper ↗ |
| 2 | Seed1.6-vision | 62.2 | 2025 | paper ↗ |
| 3 | Qwen3-Omni-30B | 61.3 | 2025 | paper ↗ |
| 4 | Nemotron Nano V2 VL | 61.2 | 2025 | paper ↗ |
| 5 | Gemini 2.5 Pro | 59.3 | 2025 | paper ↗ |
| 6 | minicpm-v-4.5-8b | 58.8 | 2025 | paper ↗ |
| 7 | sail-vl2-8b | 57.6 | 2025 | paper ↗ |
| 8 | llama-3.1-nemotron-nano-vl-8b | 56.4 | 2025 | paper ↗ |
| 9 | GPT-4o | 55.5 | 2025 | paper ↗ |
| 10 | ovis2.5-8b | 54.1 | 2025 | paper ↗ |
Didn't find the model, metric, or dataset you needed? Tell us in one line. We read every message and reply within 48 hours.
4 datasets tracked for this task.
Still looking for something on General OCR Capabilities? A missing model, a stale score, a benchmark we should cover — drop it here and we'll handle it.
Real humans read every message. We track what people are asking for and prioritize accordingly.