head to head · open source

PaddleOCR vs headroom

PaddleOCR has 89,729 GitHub stars, 11,355 forks, 243 open issues and last shipped 2 days ago. headroom has 72,745 stars, 5,589 forks, 643 open issues and last shipped yesterday. PaddleOCR leads on adoption by 23% (89,729 vs 72,745 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.

PaddleOCR ★ 90K headroom ★ 73K category AI & Machine Learning

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Side by side

PaddleOCR headroom
GitHub stars ★ 90K ★ 73K
License Apache-2.0 Apache-2.0
Written in Python Python
Last push 2026-09-16 2026-09-17
Forks ⑂ 11K ⑂ 5.6K
Self-hosting Yes Yes
Data ownership Your server Your server

pick PaddleOCR if

  • You weight community size — 90K 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

full PaddleOCR profile →

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

full headroom profile →

About PaddleOCR

PaddleOCR is an Apache 2.0 Python OCR and document AI toolkit that converts PDFs and images into structured, LLM ready JSON or Markdown across more than 100 languages, and it is built for developers who need to feed documents into RAG pipelines, agents, and document parsing services.

read the full PaddleOCR overview →

About headroom

Headroom is an Apache 2.0 Python library, local proxy, agent wrapper and MCP server that compresses tool outputs, logs, files, RAG chunks and conversation history before they reach an LLM, and it is built for developers running AI coding agents or LLM applications who want to cut token usage without changing the answers they get.

read the full headroom overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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Compare either of these against the rest of the AI Development Platforms field.

PaddleOCR vs Dify PaddleOCR vs langchain PaddleOCR vs ponytail PaddleOCR vs generative-ai-for-beginners PaddleOCR vs graphify PaddleOCR vs claude-mem PaddleOCR vs ragflow PaddleOCR vs Agent-Reach PaddleOCR vs Mem0 PaddleOCR vs daily_stock_analysis PaddleOCR vs LiteLLM PaddleOCR vs Multica

Frequently asked questions

Is PaddleOCR or headroom more popular?

PaddleOCR has 89,729 GitHub stars and headroom has 72,745. 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 (89,729 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.