
PaddleOCR
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Sep 2026
PaddleOCR is the workhorse of open source OCR. It comes out of Baidu's PaddlePaddle ecosystem and reads text from images and documents in over 100 languages. The newer pieces go further: PP-StructureV3 pulls layout and tables into Markdown or JSON, and PaddleOCR-VL is a small vision-language model that parses whole documents including formulas, tables, seals, and charts. Apache 2.0, free, and cleared for commercial use.
It runs on CPU or GPU, so you do not strictly need a graphics card to start, though a GPU helps at volume. The PP-OCRv6 models claim a fivefold CPU speedup over v5 with better accuracy, and PaddleOCR.js runs the older PP-OCRv5 model right in the browser. No server at all is also an option: the official site offers a free hosted API, capped at 3,000 pages per model per day, with a Baidu AI Studio token.
For most teams replacing a paid OCR API, this is the first tool to try. It matches the core job: text, tables, layout. Solo to large teams: free. docling-project/docling is the alternative when the goal is feeding documents to an LLM.
The catch is complexity. It is a big toolkit with many models, versions, and configuration options, and the docs lean Chinese-first in places. The repo has also been quiet since its June 2026 release. Budget the setup time.
Free vs Self-Hosted vs Paid
fully freeFree: Apache 2.0, fully open source, every model and tool included, and the model weights are Apache 2.0 too. Commercial use is fine. The official site also runs a free hosted API: up to 3,000 pages per model per day, the first 100 pages of any file, with a Baidu AI Studio access token. Higher quotas are by application, still free.
Self-hosted: Runs on CPU or GPU. Python install plus model weights: PP-OCRv6 for text, PP-StructureV3 for layout and tables, PaddleOCR-VL for full document parsing. A GPU speeds things up at volume but is not required to start.
Paid: No paid tier found, from the project or on the hosted API. Your only cost is the compute you run it on.
Free and Apache 2.0, commercial use included. Runs on plain CPU or GPU, and there is a free hosted API capped at 3,000 pages a day per model.
What to do by team size
- Solo
- free; the hosted API is the fastest way to try it
- Small team
- free
- Medium team
- free; self-host once you pass the hosted API's daily cap
- Large team
- free; budget GPU capacity and setup time
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