docling vs pdfminer.six
Document conversion and PDF extraction compared
docling converts documents across many formats into structured content for downstream workflows, while pdfminer.six focuses on extracting and analyzing PDF content. Both offer Python libraries and command-line tools, but docling emphasizes broad-format ingestion and exports, whereas pdfminer.six provides detailed PDF-focused analysis.
docling: Parse Documents for AI Workflows
Docling converts documents from formats such as PDF, Office files, images, and audio into structured representations and exports. It suits developers building document-processing and generative AI pipelines that need format coverage, OCR, or local execution.
pdfminer.six: Extract PDF Content with PDFMiner
pdfminer.six is a community-maintained fork of PDFMiner, built for extracting and analyzing content from PDF documents. Use its Python library or command-line tool to retrieve text and layout details from PDFs.
| docling | pdfminer.six | |
|---|---|---|
| Language | Python | Python |
| License | MIT | MIT |
| Stars | 68.3k | 7k |
| Forks | 5k | 1k |
| Last analyzed | Oct 3, 2026 | Oct 16, 2026 |
Key differences
- docling handles formats including office files, images, audio, video, email, and EPUB; pdfminer.six is focused on PDFs.
- docling can export to formats such as Markdown, HTML, and lossless JSON; pdfminer.six extracts PDF content as text, images, HTML, or hOCR.
- docling offers OCR and extracts PDF layout, reading order, tables, code, and formulas; pdfminer.six analyzes text positions, fonts, colors, and page layout.
- docling supports local processing and integrations with AI frameworks; pdfminer.six provides a Python API and CLI for PDF workflows.
- Both projects use Python and MIT licenses, but docling reports 68.3k stars and pdfminer.six reports 7k stars.
- docling notes that capabilities vary by format and pipeline; pdfminer.six describes PDF-1.7 support as nearly complete and notes limited maintainer availability.
Choose docling if you…
- need to process a mixed collection of documents beyond PDFs.
- want OCR, a unified document representation, or exports for AI workflows.
- need local processing for sensitive or air-gapped environments.
Choose pdfminer.six if you…
- need PDF-focused text, layout, font, or color analysis in a Python workflow.
- want to extract embedded images, table of contents, tagged content, or AcroForm data.
- work with PDFs that use CJK languages or vertical writing.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.