dots.ocr (dots.mocr) is free, with no paid plan attached. LangExtract (Google) is free, with no paid plan attached. Both are listed under AI OCR & Document Extraction, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.
dots.ocr (dots.mocr) is free, with no paid plan attached and is listed for 3B vision-language model for layout parsing across many scripts. LangExtract (Google) is free, with no paid plan attached and is listed for python library extracting structured data from unstructured text with LLMs. Both sit in AI OCR & Document Extraction.
Neither — dots.ocr (dots.mocr) and LangExtract (Google) are both free, so the choice comes down to capability rather than cost. Both entries list what they uniquely do above.
Choose dots.ocr (dots.mocr) if you need 3B vision-language model for layout parsing across many scripts; choose LangExtract (Google) if you need python library extracting structured data from unstructured text with LLMs. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.
| dots.ocr (dots.mocr) | LangExtract (Google) | |
|---|---|---|
| Pricing tier | Free | Free |
| Free to start | Yes | Yes |
| Category | Research & Learning | Research & Learning |
| Type | AI OCR & Document Extraction | AI OCR & Document Extraction |
| Listed capabilities |
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| Tags | dots.ocr, dots ocr, multilingual ocr model, open source document layout parsing, rednote ocr, xiaohongshu ocr | langextract, google langextract, extract structured data from text llm, source grounded extraction, gemini extraction library |
| Website | github.com | github.com |
| Full page | dots.ocr (dots.mocr) details → | LangExtract (Google) details → |
| Alternatives | dots.ocr (dots.mocr) alternatives → | LangExtract (Google) alternatives → |