Crawl4AI vs paddleocr
Two of the top projects in Data and scraping for AI, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
Crawl4AI
Python web crawler that converts pages to LLM-ready Markdown and JSON
paddleocr
OCR and document parsing toolkit that outputs Markdown and JSON from PDFs and images
Verdict
Crawl4AI ranks higher, 72 to 54. Of the 5 score parts we measure for both, Crawl4AI leads on 2, paddleocr on 1 and 2 are even.
- Adoptionpaddleocr leads by 13 points, 81 to 68.
- FreshnessEven at 100.
- MaintenanceCrawl4AI leads by 52 points, 81 to 29: a wide gap.
- Easy to runCrawl4AI leads by 34 points, 67 to 33: a wide gap.
- Agent-readyEven at 0.
Pick Crawl4AI if you are
Developers feeding web content into RAG, agents and data pipelines
- Schema-based CSS/XPath extraction runs without any LLM call
- Fit Markdown filters (pruning, BM25, LLM) strip menus and boilerplate
Pick paddleocr if you are
Developers feeding PDFs and scans into RAG or agent pipelines
- Three PP-OCRv6 tiers (1.5M, 7.7M, 34.5M params) cover edge to server
- One PP-OCRv6 model handles 50 languages; PaddleOCR-VL covers 111
| What we compare | Crawl4AI | paddleocr |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 68, popular | 81, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 81, healthy | 29, weak |
| Easy to run | 67, easy | 33, some setup |
| Agent-ready | 0, none | 0, none |
| Facts from GitHub and the README | ||
| Stars | 85.4k | 91k |
| License | Apache-2.0 (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Sep 2026 |
| Last release | Sep 2026 | Jun 2026 |
| Language | Python | Python |
| Docker | Yes | No |
| GPU | Not needed | Optional |
| arm64 or Apple Silicon | Mentioned | Not stated |
Crawl4AI
Crawl4AI is a Python library, CLI (`crwl`) and Docker REST server that drives Playwright browsers (Chromium, Firefox, WebKit) to turn web pages into clean or filtered Markdown. It extracts structured data with CSS/XPath/regex schemas without an LLM, or through any LiteLLM-supported provider into a typed JSON schema. It also supports deep crawls, adaptive crawling and batch fetching. A hosted Crawl4AI Cloud with search and answer endpoints is sold separately.
Who it is for: Developers feeding web content into RAG, agents and data pipelines
Strengths
- Schema-based CSS/XPath extraction runs without any LLM call
- Fit Markdown filters (pruning, BM25, LLM) strip menus and boilerplate
- Persistent profiles, CDP remote browsers, rotating proxies and stealth mode
- Docker server exposes /md, /crawl, /screenshot, /pdf, plus MCP, dashboard and playground
Weaknesses
- Search, SERP and answer endpoints exist only in the paid hosted cloud
- Bot-wall handling when self-hosted depends on your own proxies and settings
- Needs a Playwright browser install via crawl4ai-setup
- README asks for attribution when you use it
- no GPU
- Docker + Compose
- Needs Playwright browsers (Chromium), Docker (optional), LLM provider API key (optional)
- Models: LiteLLM providers, OpenAI, Ollama
- port 11235
paddleocr
PaddleOCR runs text recognition (PP-OCRv6) and document parsing (PaddleOCR-VL 0.9B VLM, PP-StructureV3) on PDFs and images, producing Markdown or JSON for RAG pipelines. It runs on CPU, NVIDIA GPU, Kunlunxin XPU and other accelerators, with ONNX, OpenVINO, TensorRT and Transformers backends. Models are on HuggingFace and ModelScope.
Who it is for: Developers feeding PDFs and scans into RAG or agent pipelines
Strengths
- Three PP-OCRv6 tiers (1.5M, 7.7M, 34.5M params) cover edge to server
- One PP-OCRv6 model handles 50 languages; PaddleOCR-VL covers 111
- Outputs Markdown, JSON and DOCX; PP-StructureV3 returns table cell and text coordinates
- Multiple inference backends: Paddle, Transformers, ONNX Runtime, OpenVINO, TensorRT, plus C++ deployment
Weaknesses
- Depends on the PaddlePaddle framework; GPU installs need matching CUDA builds
- Benchmark claims such as 96.3% on OmniDocBench are the authors' own
- Python support listed as 3.8 to 3.12 only
- Several pipelines and models, so choosing between PP-OCR, VL and StructureV3 takes reading
- GPU optional
- Needs PaddlePaddle
- Models: PP-OCRv6, PaddleOCR-VL-1.6, PP-StructureV3, HPD-Parsing, ONNX
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