dots.ocr or DeepSeek-OCR: which parses documents better for you
These are models of the same class: both about 3B, both need a GPU, and both turn scans into Markdown for search and RAG. dots.ocr from rednote hilab is MIT-licensed, is marked in the catalog as supporting Russian, and handles text, tables, formulas and reading order in one pass, while dots.mocr-svg converts charts and diagrams into vector SVG. DeepSeek-OCR compresses a page into a small number of visual tokens, which is why it is chosen for bulk processing; DeepSeek-OCR is MIT, version 2 is Apache 2.0, and it is available in Ollama, which dots.ocr is not. The catalog has no Russian-language data for DeepSeek-OCR.
Comparison based on catalog data
| Parameter | dots.ocr | DeepSeek-OCR |
|---|---|---|
| Category | Documents and OCR | Documents and OCR |
| Developer | rednote hilab (Xiaohongshu), China | DeepSeek, China |
| Releases | Jul 2025 – Mar 2026 | Oct 2025 – Jan 2026 |
| Sizes | about 3B | about 3B |
| Hardware | Laptop, 1 GPU | Laptop, 1 GPU |
| Commercial use | Commercial use allowed | Commercial use allowed |
| License | MIT | DeepSeek-OCR: MIT; DeepSeek-OCR 2: Apache 2.0 |
| Russian | Supported | Not stated |
| Ollama | No | Yes |
| Without GPU | No | No |
| Tasks |
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Choose dots.ocr if
- Your documents are in Russian: the catalog marks dots.ocr as supporting it
- You need charts and diagrams as vectors: dots.mocr-svg outputs SVG
- Reading order across complex layouts matters, in a single pass
Choose DeepSeek-OCR if
- You have a large volume of scans: pages compress into few visual tokens
- You want to install the model through Ollama
- You need an Apache 2.0 version: that is DeepSeek-OCR 2 (2026-01)
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