docling 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.
docling
Python library and CLI that converts PDFs, Office files and more into structured text
paddleocr
OCR and document parsing toolkit that outputs Markdown and JSON from PDFs and images
Verdict
docling ranks higher, 70 to 54. Of the 5 score parts we measure for both, docling leads on 3, paddleocr on 1 and 1 is even.
- Adoptionpaddleocr leads by 29 points, 81 to 52: a wide gap.
- FreshnessEven at 100.
- Maintenancedocling leads by 52 points, 81 to 29: a wide gap.
- Easy to rundocling leads by 17 points, 50 to 33: a wide gap.
- Agent-readydocling leads by 85 points, 85 to 0: a wide gap.
Pick docling if you are
Developers preparing documents for RAG and LLM pipelines
- Wide input coverage: PDF, Office, ODF, EPUB, email, Apple iWork, XBRL, audio, video
- Local execution suits sensitive data and air-gapped environments
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 | docling | paddleocr |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 52, popular | 81, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 81, healthy | 29, weak |
| Easy to run | 50, easy | 33, some setup |
| Agent-ready | 85, ready | 0, none |
| Facts from GitHub and the README | ||
| Stars | 68.8k | 91k |
| License | MIT (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Sep 2026 |
| Last release | Oct 2026 | Jun 2026 |
| Language | Python | Python |
| Docker | Yes | No |
| GPU | Optional | Optional |
| arm64 or Apple Silicon | Mentioned | Not stated |
docling
Docling parses PDF, DOCX, PPTX, XLSX, HTML, EPUB, images, audio and other formats into a unified DoclingDocument, with PDF layout, reading order, table structure, code and formula recognition. It exports to Markdown, HTML, DocLang, DocTags and lossless JSON. It runs locally via a CLI or Python API, with OCR, VLM support (GraniteDocling), an MCP server and a docling-serve API server.
Who it is for: Developers preparing documents for RAG and LLM pipelines
Strengths
- Wide input coverage: PDF, Office, ODF, EPUB, email, Apple iWork, XBRL, audio, video
- Local execution suits sensitive data and air-gapped environments
- Integrations with LangChain, LlamaIndex, Crew AI and Haystack
- Ships a CLI, Python API, MCP server and docling-serve HTTP server
Weaknesses
- Hardware requirements (RAM, GPU) are not stated in the README
- Individual models carry their own licenses, separate from the MIT codebase
- Metadata extraction and chemistry understanding are listed as coming soon
- Requires Python 3.10 or higher; 3.9 support was dropped in 2.70.0
- GPU optional
- Docker
- Models: GraniteDocling, VLMs, OCR engines, ASR models
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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