---
title: "PaddleOCR"
type: "tool"
slug: "paddlepaddle-paddleocr"
canonical_url: "https://www.graphcanon.com/tools/paddlepaddle-paddleocr"
github_url: "https://github.com/PaddlePaddle/PaddleOCR"
homepage_url: "https://www.paddleocr.com"
stars: 84919
forks: 10978
primary_language: "Python"
license: "Apache-2.0"
categories: ["data-retrieval"]
tags: ["ai4science", "document-translation", "pdf-extractor-rag", "kie", "paddleocr-vl", "chineseocr", "ocr", "document-parsing"]
updated_at: "2026-07-07T18:58:25.588995+00:00"
---

# PaddleOCR

> PaddleOCR: A powerful OCR toolkit for transforming PDFs/images into structured data

A lightweight OCR toolkit that converts images/PDF documents into LLM-friendly structured data formats like JSON or Markdown, supporting over 100 languages. Features include document parsing with vision-language models and multilingual text recognition.

## Facts

- Repository: https://github.com/PaddlePaddle/PaddleOCR
- Homepage: https://www.paddleocr.com
- Stars: 84,919 · Forks: 10,978 · Open issues: 220 · Watchers: 553
- Primary language: Python
- License: Apache-2.0
- Last pushed: 2026-06-26T09:31:42+00:00

## Categories

- [Data & Retrieval](/categories/data-retrieval.md)

## Tags

ai4science, document-translation, pdf-extractor-rag, kie, paddleocr-vl, chineseocr, ocr, document-parsing

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## README (excerpt)

```text
<div align="center">
  <p>
      <img width="800" src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/main/images/paddleocr/README/Banner.png" alt="Star-history">
  </p>



<h3>Global Leading OCR Toolkit & Document AI Engine</h3>

English | [简体中文](./readme/README_cn.md) | [繁體中文](./readme/README_tcn.md) | [日本語](./readme/README_ja.md) | [한국어](./readme/README_ko.md) | [Français](./readme/README_fr.md) | [Русский](./readme/README_ru.md) | [Español](./readme/README_es.md) | [العربية](./readme/README_ar.md)













</div>






**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 vision-language model for document parsing. It achieves 96.3% accuracy on OmniDocBench v1.6, leads in text, formula, and table recognition, and shows significantly enhanced capabilities in ancient documents, rare characters, seals, and charts, with structured outputs in **Markdown** and **JSON** formats.
* **Structure-Aware Conversion**: Powered by **PP-StructureV3**, seamlessly convert complex PDFs and images into **Markdown** or **JSON**. Unlike the PaddleOCR-VL series models, it provides more fine-grained coordinate information, including table cell coordinates, text coordinates, and more.
* **Production-Ready Efficiency**: Achieve commercial-grade accuracy with an ultra-small footprint. Outperforms numerous closed-source solutions in public benchmarks while remaining resource-efficient for edge/cloud deployment.

### 🔍 Universal Text Recognition (Scene OCR)
> *The global gold standard for high-speed, multilingual text spotting.*

* **100+ Languages Supported**: Native recognition for a vast global library. **PP-OCRv6** supports 50 languages with a single unified model (Chinese, English, Japanese, and 46 Latin-script languages) — no model switching needed for multilingual documents.
* **Complex Element Mastery**: Beyond standard text recognition, we support **natural scene text spotting** across a wide range of environments, including IDs, street views, books, and industrial components
* **Performance Leap**: PP-OCRv6 achieves **+4.6% detection** and **+5.1% recognition** accuracy over PP-OCRv5, surpassing mainstream Vision-Language Models. 5.2× CPU inference speedup end-to-end.

<div align="center">
  <p>
      <img width="100%" src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/main/images/paddleocr/README/Arch.jpg" alt="PaddleOCR Architecture">
  </p>
</div>

### 🛠️ Developer-Centric Ecosystem
* **Seamless Integration**: The premier choice for the AI Agent ecosystem—deeply integrated with **Dify, RAGFlow, Pathway, and Cherry Studio**.
* **LLM Data Flywheel**: A complete pipeline to build high-quality datasets, providing a sustainable "Data Engine" for fine-tuning Large Language Models.
* **One-Click Deployment**: Supports various hardware backends (NVIDIA GPU, Intel CPU, Kunlunxin XPU, and diverse AI Accelerators).


## 📣 Recent updates

### 🔥 2026.06.11: Release of PaddleOCR 3.7.0
- PP-OCRv6 highlights:

    - **Accuracy boost**: Medium tier achieves +4.6% detection and +5.1% recognition over PP-OCRv5_server, surpassing mainstream VLMs (Qwen3-VL-235B, GPT-5.5) with only 34.5M parameters.
    - **50 languages unified**: Single model covers Chinese, English, Japanese, and 46 Latin-script languages — no model switching needed.
    - **Specialized scenarios**: Major improvements in digital displays, dot-matrix characters, tire prints, and industrial text recognition.
    - **Faster inference**: 5.2× CPU speedup (OpenVINO), 6.1× on Apple M
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/paddlepaddle-paddleocr`](/api/graphcanon/tools/paddlepaddle-paddleocr)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_