Pyyan / Compare / dots.ocr vs GLM-OCR vs Mistral OCR
dots.ocr vs GLM-OCR vs Mistral OCR
3 of 5OCR & Document AI · verified 13 Aug 2026
| Specification | dots.ocr | GLM-OCR | Mistral OCR |
|---|---|---|---|
| Summary | Small, multilingual, layout-aware. | Currently the top scorer on document parsing. | A hosted API built for document ingestion. |
| OmniDocBench | ~93 | 94.6 | ~92 |
| Open weights | Yes | Yes | No |
| Handles | Layout, 100+ languages | Tables, formulas, handwriting | Tables, images, equations |
| Licence | MIT | Open weights | Proprietary |
| Kind | Vision language model | Vision language model | Hosted API |
| Category | OCR & Document AI | OCR & Document AI | OCR & Document AI |
| Official | Xiaohongshu ↗ | Zhipu AI ↗ | Mistral AI ↗ |
Highlighted rows are where these differ.
dots.ocr
- Layout and content in one pass
- Strong for its size
Best for multilingual layout parsing.
GLM-OCR
- Ahead of Gemini 3 Pro and GPT-5.2 on the same benchmark
- 94.0 on OCRBench
Best for complex documents end to end.
Mistral OCR
- Priced per page
- Returns structured markdown
Best for teams who want no infrastructure.