Docling vs Marker

Docling is free, with no paid plan attached. Marker is free, with no paid plan attached. Both are listed under AI OCR & Document Extraction, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.

Docling vs Marker — straight answers

Docling vs Marker: what is the difference?

Docling is free, with no paid plan attached and is listed for MIT-licensed, 64.7k GitHub stars, IBM Research-originated, now under LF AI & Data Foundation. Marker is free, with no paid plan attached and is listed for apache-2.0 code, 38.7k GitHub stars, converts PDFs/DOCX/PPTX/XLSX to markdown/JSON. Both sit in AI OCR & Document Extraction.

Is Docling or Marker cheaper to start with?

Neither — Docling and Marker are both free, so the choice comes down to capability rather than cost. Both entries list what they uniquely do above.

Which should I choose, Docling or Marker?

Choose Docling if you need MIT-licensed, 64.7k GitHub stars, IBM Research-originated, now under LF AI & Data Foundation; choose Marker if you need apache-2.0 code, 38.7k GitHub stars, converts PDFs/DOCX/PPTX/XLSX to markdown/JSON. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

Docling compared with Marker: pricing tier, category, listed capabilities and links.
 DoclingMarker
Pricing tierFreeFree
Free to startYesYes
CategoryResearch & LearningResearch & Learning
TypeAI OCR & Document ExtractionAI OCR & Document Extraction
Listed capabilities
  • MIT-licensed, 64.7k GitHub stars, IBM Research-originated, now under LF AI & Data Foundation
  • Advanced PDF layout + table structure recognition, local execution
  • Exports to Markdown/HTML/JSON, integrates with LangChain/LlamaIndex
  • Apache-2.0 code, 38.7k GitHub stars, converts PDFs/DOCX/PPTX/XLSX to markdown/JSON
  • 76.0% accuracy on the olmocr-bench benchmark
  • Runs on GPU, CPU, or Apple Silicon; optional LLM-boosted accuracy mode
Tagsdocling, ibm document ai, pdf parsing open source, document conversion, free ocrmarker, datalab, pdf to markdown, open source document parsing, surya ocr
Websitegithub.comgithub.com
Full pageDocling details →Marker details →
AlternativesDocling alternatives →Marker alternatives →

dots.ocr (dots.mocr)

AI OCR & Document Extraction
freeNew
  • 3B vision-language model for layout parsing across many scripts
  • Converts charts and diagrams into SVG code
  • Scores 83.9 on olmOCR-bench
  • MIT licensed with free live demo

LangExtract (Google)

AI OCR & Document Extraction
freeNew
  • Python library extracting structured data from unstructured text with LLMs
  • Maps each extraction to its exact source span
  • Works with Gemini, OpenAI and local Ollama models
  • Interactive HTML visualization of results

MinerU

AI OCR & Document Extraction
freeNew
  • Parses PDFs, images and Office files into Markdown, JSON, HTML or LaTeX
  • Runs fully locally with OCR, table and formula recognition
  • Free hosted web app at mineru.net plus agent-ready outputs
  • Version 4.0 adds four parsing quality tiers

olmOCR

AI OCR & Document Extraction
free
  • Apache 2.0 open-source OCR toolkit from Ai2, 19.3k GitHub stars
  • Vision-language-model based, handles equations/tables/multi-column layout
  • Runs at a fraction of commercial OCR cost on a 7B model

PaddleOCR-VL

AI OCR & Document Extraction
freeNew
  • 1B-parameter document parsing VLM (NaViT encoder + ERNIE-4.5-0.3B)
  • Handles text, tables, formulas, charts and handwriting
  • Supports 109 languages including Hindi and Arabic
  • Apache 2.0; newer PaddleOCR-VL-1.6 available

DeepSeek-OCR

AI OCR & Document Extraction
freeNew
  • Vision-language OCR that compresses document context optically
  • Document-to-Markdown, layout detection and figure parsing
  • Multiple resolution modes up to 1280x1280
  • MIT license; DeepSeek-OCR2 released Jan 2026