PaddleOCR

What is PaddleOCR?

PaddleOCR from Baidu's PaddlePaddle team recognises text in images and PDFs in 100+ languages (PP-OCR models) and parses whole documents, including layout, tables and formulas, into Markdown or JSON (PP-StructureV3 and the PaddleOCR-VL vision-language models). It is used as a Python library and CLI, and any pipeline can be served as an HTTP API through the PaddleX serving plugin. It runs on CPU, NVIDIA GPU and other accelerators.

Where it fits in a 10–200 person business

• Digitise scanned invoices, forms, contracts and ID documents into searchable text
• Pre-process PDFs and images into Markdown for a RAG knowledge base
• Read text on industrial parts, labels and displays in images from the shop floor

These use cases are our editorial suggestions, not claims made by the project.

Can a business use PaddleOCR? (license)

This is a plain-English summary of the license text, not legal advice. Third-party models you run with it have their own licenses.

Data & compliance: does PaddleOCR phone home?

Checked against the project's own docs and repository on Oct 23, 2026. "Not documented" means we could not find the answer in official sources; it does not mean the feature is missing or that no data is sent. Third-party services you connect (model APIs, vector databases, search engines) have their own data policies. Compare all apps.

What hardware does PaddleOCR need?

The project does not publish a minimum CPU/RAM figure, so we leave the official value blank rather than guess.

GPU: Optional. The server uses a GPU by default if available, otherwise the CPU.

No official server RAM or disk requirements published. Needs depend on the pipeline (light OCR models versus PP-StructureV3 or PaddleOCR-VL document parsing).

Source: www.paddleocr.ai/latest/en/version3.x/inference_deployment/serving/serving.html

How much does it cost to host PaddleOCR per month?

How to deploy PaddleOCR

Method: pip + PaddleX serving (HTTP API)

python -m pip install paddlepaddle==3.2.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/
python -m pip install paddleocr
paddlex --install serving
paddlex --serve --pipeline OCR
# HTTP API on :8080; GPU wheels are listed on the PaddlePaddle install page

From the official instructions: www.paddleocr.ai/latest/en/version3.x/inference_deployment/serving/serving.html. Always check the source for the current version before you run it.

Known gotchas when self-hosting PaddleOCR

• Serving runs through the PaddleX CLI and uses PaddleX pipeline names, such as OCR for the general OCR pipeline. To change models, batch size or device, pass a PaddleX pipeline config file to --pipeline. source
• The Triton-based high-stability serving may not match the performance of the old 2.x PaddleServing deployment, according to the docs. source
• Images and other binary results come back inline as Base64 by default, which inflates large or multi-page responses. URL return currently only supports Baidu BOS object storage. source
• Different inference engines can have conflicting dependencies, so the docs recommend installing only one per environment. Optional dependency groups like doc-parser need Python 3.9+. source

Alternatives in Document processing

• MinerU Document parser that converts PDFs, scans and Office files into clean Markdown or JSON for LLMs and RAG. Compare MinerU vs PaddleOCR
• Paperless-AI AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). Compare PaddleOCR vs Paperless-AI

Sources

• GitHub repository: github.com/PaddlePaddle/PaddleOCR
• Official documentation: www.paddleocr.ai/
• License text: github.com/PaddlePaddle/PaddleOCR/blob/main/LICENSE
• Hardware requirements, Deploy instructions, Gotcha 1, Gotcha 2, Gotcha 3: www.paddleocr.ai/latest/en/version3.x/inference_deployment/serving/serving.html
• Gotcha 4: www.paddleocr.ai/latest/en/version3.x/inference_deployment/local_inference/inference_engine.html
• Hetzner Cloud pricing (cost estimate): www.hetzner.com/cloud/regular-performance
• GitHub stars, commits and releases: GitHub REST API, fetched Oct 23, 2026