head to head · open source
PaddleOCR vs R2R
PaddleOCR has 92,231 GitHub stars, 11,616 forks, 243 open issues and last shipped 2 months ago. R2R has 8,057 stars, 651 forks, 126 open issues and last shipped 12 months ago. PaddleOCR leads on adoption by 1,045% (92,231 vs 8,057 stars). PaddleOCR is written in Python under Apache-2.0; R2R is written in Python under MIT. PaddleOCR has attracted 13% as many forks as stars, R2R 8%. PaddleOCR was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| PaddleOCR | R2R | |
|---|---|---|
| GitHub stars | ★ 92K | ★ 8.1K |
| License | Apache-2.0 | MIT |
| Written in | Python | Python |
| Last push | 2026-09-16 | 2025-11-07 |
| Forks | ⑂ 12K | ⑂ 651 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick PaddleOCR if
- You weight community size — 92K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick R2R if
- You want the R2R feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and R2R fits your workflow better
About PaddleOCR
Global Leading OCR Toolkit & Document AI Engine English 简体中文 繁體中文 日本語 한국어 Français Русский Español العربية PaddleOCR converts PDF documents and images into structured, LLM ready data (JSON/Markdown) with industry leading accuracy. With 70k+ Stars and trusted by top tier projects like Dify, RAGFlow, and Cherry Studio, PaddleOCR is the bedrock for building intelligent RAG and Agentic applications. 🚀 Key Features 📄 Intelligent Document Parsing (LLM Ready) Transforming messy visuals into structured data for the LLM era. SOTA Document VLM : Featuring PaddleOCR VL 1.6 (0.9B) , the industry's leading lightweight…
read the full PaddleOCR overview →
About R2R
The most advanced AI retrieval system. Agentic Retrieval Augmented Generation (RAG) with a RESTful API. Docs · Report Bug · Feature Request · Discord About R2R is an advanced AI retrieval system supporting Retrieval Augmented Generation (RAG) with production ready features. Built around a RESTful API, R2R offers multimodal content ingestion, hybrid search, knowledge graphs, and comprehensive document management. R2R also includes a Deep Research API , a multi step reasoning system that fetches relevant data from your knowledgebase and/or the internet to deliver richer, context aware answers for complex queries…
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Frequently asked questions
Is PaddleOCR or R2R more popular?
PaddleOCR has 92,231 GitHub stars and R2R has 8,057. PaddleOCR has the larger community by that measure.
Are PaddleOCR and R2R free?
Both are open source. PaddleOCR is licensed under Apache-2.0 and R2R under MIT. Neither carries a licence fee.
What is the difference between PaddleOCR and R2R?
PaddleOCR is written in Python and R2R in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, PaddleOCR or R2R?
Choose PaddleOCR if you want the larger community (92,231 stars) or its Apache-2.0 licence terms. Choose R2R if its feature set, stack or MIT licence fits better. Both are self-hostable.