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✦ Free & open sourceMarketing

PaddleOCR

Turn PDFs and images into structured Markdown or JSON data for LLMs.

Convert documents into LLM-ready data

A powerful OCR toolkit bridging the gap between images, PDFs, and LLMs across 100+ languages.

Free forever · open source · Apache-2.0
✓ Needs IT✓ Browser-based✓ Real-time collaboration
8.3
ZEKAI
Essential document AI toolkit
Free & open source · Marketing
Ease of setup5
Usefulness9
Maintenance9.5
Community9.8
★ 90,937
GITHUB
Sep 2026
UPDATED
Apache-2.0
LICENSE
🛠 Don't want to self-host? We can set it up →
⚡ Quick answer

PaddleOCR is a document AI engine that extracts text, tables, and formulas from PDFs and images into structured Markdown or JSON. It suits AI and content professionals building retrieval-augmented generation or agentic workflows.

Runs on
Cross-platform
Hosting
Self-host
Languages
Python
License
Apache-2.0

What it is

It parses complex documents using vision-language models like PaddleOCR-VL and the PP-StructureV3 engine for fine-grained coordinate mapping. It also provides universal text recognition across 100+ languages through unified PP-OCR models.

Who it's for

It suits machine learning engineers and developers building document processing pipelines or RAG applications. It is not built for non-technical users looking for a plug-and-play desktop PDF converter.

Key features

Intelligent Document Parsing

Transforms visual layouts into structured Markdown and JSON formats.

Universal Text Recognition

Supports 50 languages in a single model without requiring model switching.

Structure-Aware Conversion

Extracts detailed coordinate information including table cells and text blocks.

Flexible Inference Backends

Deploys across NVIDIA GPUs, Intel CPUs, Kunlunxin XPUs, and various accelerators.

How to start

Up and running in 3 steps

1
Install the Python package from PyPI for local environment usage
2
Choose a model tier or VLM variant depending on your accuracy and hardware needs
3
Configure inference backends and integrate the parsing pipeline into your application
Real talk

Our honest verdict

What's great

  • Supports over 100 languages with unified multilingual recognition models
  • Provides fine-grained coordinate mapping for table cells and text elements
  • Integrates directly into AI agent ecosystems like Dify and RAGFlow
  • Offers multiple model tiers ranging from tiny edge devices to server GPUs

Where it falls short

  • Requires significant technical skill to configure, integrate, and run locally
  • Running vision-language models at scale demands dedicated hardware resources
  • Python-centric ecosystem requires managing dependencies and inference backends
Cost

Pricing & license

Free under the Apache-2.0 licence, with no paid hosted option mentioned in the repository. The only cost is running the hardware infrastructure yourself.

Paid work

Open remote AI-training roles

880 open remote AI-training roles, updated November 15, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.

See all open roles →
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Alternatives

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Questions

FAQ

What output formats does PaddleOCR provide?

It outputs structured data in Markdown and JSON formats, complete with layout and coordinate details.

Can I run PaddleOCR on a CPU?

Yes, it supports CPU deployment alongside various hardware backends like GPUs and XPUs.

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