LangExtract (Google) vs Marker

LangExtract (Google) 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.

LangExtract (Google) vs Marker — straight answers

LangExtract (Google) vs Marker: what is the difference?

LangExtract (Google) is free, with no paid plan attached and is listed for python library extracting structured data from unstructured text with LLMs. 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 LangExtract (Google) or Marker cheaper to start with?

Neither — LangExtract (Google) 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, LangExtract (Google) or Marker?

Choose LangExtract (Google) if you need python library extracting structured data from unstructured text with LLMs; 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.

LangExtract (Google) compared with Marker: pricing tier, category, listed capabilities and links.
 LangExtract (Google)Marker
Pricing tierFreeFree
Free to startYesYes
CategoryResearch & LearningResearch & Learning
TypeAI OCR & Document ExtractionAI OCR & Document Extraction
Listed capabilities
  • 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
  • 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
Tagslangextract, google langextract, extract structured data from text llm, source grounded extraction, gemini extraction librarymarker, datalab, pdf to markdown, open source document parsing, surya ocr
Websitegithub.comgithub.com
Full pageLangExtract (Google) details →Marker details →
AlternativesLangExtract (Google) alternatives →Marker alternatives →

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

Docling

AI OCR & Document Extraction
free
  • 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

Dolphin (ByteDance)

AI OCR & Document Extraction
freeNew
  • Two-stage document-type and layout analysis then element parsing
  • Page-level and element-level parsing modes
  • Hugging Face Transformers integration
  • MIT licensed; Dolphin-v2 released Dec 2025

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

MarkItDown

AI OCR & Document Extraction
freeNew
  • Converts PDF, Office files, images, audio and HTML into LLM-friendly Markdown
  • Ships an MCP server for agents
  • Open-source Python package and CLI
  • Optional LLM-based image description

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