mineru vs docling
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.
mineru
Document parser that converts PDFs, images and Office files to Markdown and JSON
docling
Python library and CLI that converts PDFs, Office files and more into structured text
Verdict
mineru ranks higher, 78 to 76. Of the 5 score parts we measure for both, mineru leads on 2, docling on 1 and 2 are even.
- Adoptionmineru leads by 6 points, 77 to 71.
- FreshnessEven at 100.
- Maintenancemineru leads by 11 points, 99 to 88.
- Easy to runEven at 50.
- Agent-readydocling leads by 15 points, 85 to 70: a wide gap.
Pick mineru if you are
Engineers feeding PDFs and Office documents to LLM pipelines or agents
- Handles scanned PDFs, tables and formulas, with four quality tiers from fast preview to advanced
- Stable doc/tier/page/block locators allow paged reading and citation of long documents
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
| What we compare | mineru | docling |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 77, popular | 71, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 99, healthy | 88, healthy |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 81.8k | 68.9k |
| License | custom license (read the license) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Python | Python |
| Docker | Yes | Yes |
| GPU | Optional | Optional |
| arm64 or Apple Silicon | Mentioned | Mentioned |
mineru
MinerU parses PDFs, scanned images, Office, OpenDocument, EPUB, OFD, HTML and CSV files into Markdown, HTML, LaTeX, DOCX and structured content lists. It offers four parsing tiers (flash, basic, standard, advanced), a local document library with search, and page/block locators for citations. It ships a CLI, Python SDK, API, router and Gradio WebUI, plus an agent skill.
Who it is for: Engineers feeding PDFs and Office documents to LLM pipelines or agents
Strengths
- Handles scanned PDFs, tables and formulas, with four quality tiers from fast preview to advanced
- Stable doc/tier/page/block locators allow paged reading and citation of long documents
- Small models run on ONNX CPU; the VLM can run on llama.cpp, vLLM or LMDeploy
- Documents are not uploaded to the official service unless remote parsing is configured
Weaknesses
- Office, HTML, EPUB, OFD and CSV files only get flash-tier parsing; higher tiers are PDF and image only
- Docker deployment for non-NVIDIA devices is pending an update
- Highest throughput needs an NVIDIA GPU and mineru[full]; Windows needs torch installed separately
- License is reported as NOASSERTION, so terms need checking before use
- GPU optional
- Docker + Compose
- Needs Python >=3.10,<3.15, llama.cpp, vLLM or LMDeploy (VLM runtime), ONNX or Torch
- Models: MinerU VLM, ONNX small models, Torch small models, llama.cpp, vLLM
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
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