head to head · open source
PaddleOCR vs headroom
PaddleOCR has 92,143 GitHub stars, 11,613 forks, 243 open issues and last shipped 2 months ago. headroom has 78,657 stars, 6,141 forks, 643 open issues and last shipped yesterday. PaddleOCR leads on adoption by 17% (92,143 vs 78,657 stars). PaddleOCR is written in Python under Apache-2.0; headroom is written in Python under Apache-2.0. PaddleOCR has attracted 13% as many forks as stars, headroom 8%. headroom 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 | headroom | |
|---|---|---|
| GitHub stars | ★ 92K | ★ 79K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-16 | 2026-11-02 |
| Forks | ⑂ 12K | ⑂ 6.1K |
| 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 headroom if
- You want the headroom 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 headroom 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 headroom
Quickstart · Install · Proof · Agents · Docs · Discord · llms.txt AI agents / LLMs: read /llms.txt here, or fetch the live index · full docs blob . Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens. Compression runs on your machine; no prompt or file content is sent anywhere to be compressed. 10,144 → 1,260 tokens. The same FATAL found. What it does Library — compress(messages) in Python or TypeScript, inline in any app. Proxy — headroom proxy port 8787 , zero code changes, any…
read the full headroom overview →
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Frequently asked questions
Is PaddleOCR or headroom more popular?
PaddleOCR has 92,143 GitHub stars and headroom has 78,657. PaddleOCR has the larger community by that measure.
Are PaddleOCR and headroom free?
Both are open source. PaddleOCR is licensed under Apache-2.0 and headroom under Apache-2.0. Neither carries a licence fee.
What is the difference between PaddleOCR and headroom?
PaddleOCR is written in Python and headroom 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 headroom?
Choose PaddleOCR if you want the larger community (92,143 stars) or its Apache-2.0 licence terms. Choose headroom if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.