head to head · open source

Agent-Reach vs PaddleOCR

Agent-Reach has 108,014 GitHub stars, 9,640 forks, 137 open issues and last shipped 2 days ago. PaddleOCR has 92,143 stars, 11,613 forks, 243 open issues and last shipped 2 months ago. Agent-Reach leads on adoption by 17% (108,014 vs 92,143 stars). Agent-Reach is written in Python under MIT; PaddleOCR is written in Python under Apache-2.0. Agent-Reach has attracted 9% as many forks as stars, PaddleOCR 13%. Agent-Reach 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.

Agent-Reach ★ 108K PaddleOCR ★ 92K category AI & Machine Learning

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Side by side

Agent-Reach PaddleOCR
GitHub stars ★ 108K ★ 92K
License MIT Apache-2.0
Written in Python Python
Last push 2026-11-01 2026-09-16
Forks ⑂ 9.6K ⑂ 12K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agent-Reach if

  • You weight community size — 108K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full Agent-Reach profile →

pick PaddleOCR if

  • You want the PaddleOCR feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and PaddleOCR fits your workflow better

full PaddleOCR profile →

About Agent-Reach

👁️ Agent Reach 给你的 AI Agent 一键装上互联网能力 当下最稳的接入方式,替你选好、装好、体检好——接入方式会换代,你不用操心 快速开始 · English · 日本語 · 한국어 · 支持平台 · 设计理念 ❤️赞助商 想出现在这里? 点击折叠 BrowserAct 支持从 Amazon、LinkedIn、X、Google Maps 等复杂网站提取你需要的任意数据。你只需用自然语言描述抓取需求,Agent 就会基于真实浏览器自动探索并测试页面流程,生成可靠、可复用的数据采集 Bot,并返回结构化结果。无需手动构建爬虫,无需编写代码。BrowserAct 内置隐身浏览、验证码处理和高质量住宅代理,帮助你更稳定地完成复杂网页数据采集。新用户注册即送 1000 积分, 立即免费试用 。 在腾讯云 Lighthouse 秒级部署 OpenClaw 全能助手,可通过对话丝滑接入 Agent Reach,给你的 OpenClaw 一键装上互联网能力。 CoreClaw 网页抓取平台与现成数据采集工具,CoreClaw 提供 100+ 现成数据采集工具,支持 Amazon、TikTok、Google Maps、Instagram、Facebook、YouTube 等平台,无需代码,支持 JSON/CSV 导出,仅对成功结果计费。 免费$3测试! 优刻得星图astraflow大模型…

read the full Agent-Reach overview →

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 →

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Frequently asked questions

Is Agent-Reach or PaddleOCR more popular?

Agent-Reach has 108,014 GitHub stars and PaddleOCR has 92,143. Agent-Reach has the larger community by that measure.

Are Agent-Reach and PaddleOCR free?

Both are open source. Agent-Reach is licensed under MIT and PaddleOCR under Apache-2.0. Neither carries a licence fee.

What is the difference between Agent-Reach and PaddleOCR?

Agent-Reach is written in Python and PaddleOCR 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, Agent-Reach or PaddleOCR?

Choose Agent-Reach if you want the larger community (108,014 stars) or its MIT licence terms. Choose PaddleOCR if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.