Docling vs Humata

Docling is free, with no paid plan attached. Humata is freemium — a usable free tier with paid plans above it. 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 Humata — straight answers

Docling vs Humata: 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. Humata is freemium — a usable free tier with paid plans above it and is listed for free tier: 60 pages, 10 answers, no card. Both sit in AI OCR & Document Extraction.

Is Docling or Humata cheaper to start with?

Docling is the cheaper starting point: it is free, with no paid plan attached, while Humata is freemium — a usable free tier with paid plans above it. Pricing tiers here come from the catalog, not from a promotional page.

Which should I choose, Docling or Humata?

Choose Docling if you need MIT-licensed, 64.7k GitHub stars, IBM Research-originated, now under LF AI & Data Foundation; choose Humata if you need free tier: 60 pages, 10 answers, no card. 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 Humata: pricing tier, category, listed capabilities and links.
 DoclingHumata
Pricing tierFreeFree tier + paid plans
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
  • Free tier: 60 pages, 10 answers, no card
  • Cited answers across many uploaded files at once
  • Paid tiers priced per extra page rather than per seat
Tagsdocling, ibm document ai, pdf parsing open source, document conversion, free ocrhumata, ask questions of files, document ai, chat with files, free pdf ai
Websitegithub.comhumata.ai
Full pageDocling details →Humata details →
AlternativesDocling alternatives →Humata 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