head to head · open source
PaddleOCR vs qwen-code
PaddleOCR has 92,231 GitHub stars, 11,616 forks, 243 open issues and last shipped 2 months ago. qwen-code has 28,987 stars, 3,308 forks, 1,422 open issues and last shipped yesterday. PaddleOCR leads on adoption by 218% (92,231 vs 28,987 stars). PaddleOCR is written in Python under Apache-2.0; qwen-code is written in TypeScript under Apache-2.0. PaddleOCR has attracted 13% as many forks as stars, qwen-code 11%. qwen-code 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 | qwen-code | |
|---|---|---|
| GitHub stars | ★ 92K | ★ 29K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-09-16 | 2026-11-04 |
| Forks | ⑂ 12K | ⑂ 3.3K |
| 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 qwen-code if
- You want the qwen-code feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches TypeScript
- You evaluated both and qwen-code 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 qwen-code
The open source AI coding agent for your terminal, editor, desktop, browser, and chat. 中文 Deutsch français 日本語 Русский Português (Brasil) 한국어 Why Qwen Code? Agentic out of the box — Auto Memory, Auto Skills, SubAgents, Agent Teams, and MCP. Dynamic workflows, zero setup. Open source, inside and out — The framework and the Qwen models are open source. They evolve together. No vendor lock in. Multi protocol — Supports OpenAI, Anthropic, Gemini, and Qwen APIs. Any third party provider or local model (Ollama / vLLM). Switch at runtime. Beyond the terminal — IDE plugins, Desktop app, Web UI, SDKs, and chat…
read the full qwen-code overview →
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Frequently asked questions
Is PaddleOCR or qwen-code more popular?
PaddleOCR has 92,231 GitHub stars and qwen-code has 28,987. PaddleOCR has the larger community by that measure.
Are PaddleOCR and qwen-code free?
Both are open source. PaddleOCR is licensed under Apache-2.0 and qwen-code under Apache-2.0. Neither carries a licence fee.
What is the difference between PaddleOCR and qwen-code?
PaddleOCR is written in Python and qwen-code in TypeScript. 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 qwen-code?
Choose PaddleOCR if you want the larger community (92,231 stars) or its Apache-2.0 licence terms. Choose qwen-code if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.