Conversion Quality Benchmark

We tested PDF to Markdown converters on real-world documents: API docs, research papers, technical manuals, and code-heavy PDFs. Here are the results.

Last updated: March 2026Start Converting

Feature-by-Feature Comparison

Feature	PDF for AIOurs	Marker (OSS)	Generic tools
Header hierarchy (H1-H6)	Excellent	Good	Poor
Code block detection	Excellent	Good	None
Nested list preservation	Excellent	Good	Poor
Table structure	Good	Good	None
Footnote extraction	Excellent	Poor	None
Bold / italic detection	Excellent	Good	Poor
Multi-column layout	Good	Good	Poor
Privacy (no upload)	Excellent	None	None
Speed (browser-based)	Excellent	None	Poor

Benchmarks based on testing with 10 real-world PDFs across different document types. Results may vary depending on PDF structure.

Why Conversion Quality Matters

Bad PDF conversion doesn't just look ugly. It breaks downstream workflows, produces hallucinations in AI tools, and wastes your time fixing output manually.

RAG Pipelines

Clean Markdown with preserved structure means better embeddings and more accurate retrieval for your AI applications.

Documentation Migration

Move legacy PDF docs to Markdown-based systems like Docusaurus, GitBook, or Notion without losing formatting.

AI Prompt Preparation

Copy-paste into ChatGPT, Claude, or Gemini with headers, code blocks, and lists intact for better AI responses.

What We Test

API Documentation

Technical docs with code samples, endpoint tables, and nested parameter lists.

Research Papers

Academic papers with footnotes, citations, multi-column layouts, and equations.

Technical Manuals

Product manuals with hierarchical headings, numbered procedures, and diagrams.

Financial Reports

Documents with complex tables, charts, and multi-level section structure.

See the Difference Yourself

Drop your toughest PDF and compare the output. No sign-up, no upload to servers, completely free.

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