Benchmark · Version 1

Converting a complex PDF into clean Markdown with an open-source library

This benchmark is for self-hostable open-source libraries that convert real-world PDFs into Markdown.

Benchmark overview

8Capabilities
12Scenarios
10Participating tools
What is included and excluded

How well a self-hostable open-source library turns complex PDFs into faithful Markdown that a reader can trust without opening the original.

A reader learns where a library preserves content and structure, and where it drops, reorders, invents, or weakens information. The point is not pretty output; it is whether the converted document still supports search, retrieval, QA, indexing, and human review.

In scope

  • Converting complex, real-world PDFs into Markdown with an open-source library.
  • Preserving text, reading order, headings, tables, figures, charts, scanned text, equations, and code.
  • Judging completeness, accuracy, faithfulness, and honesty against the source PDF.

Out of scope

  • Structured field extraction.
  • Web-page conversion.
  • Form filling.
  • Handwriting.
  • Document classification or routing.
  • PDF creation or editing.

Participating tools

How each tool did on the 12 scenarios in this benchmark. Each cell is one scenario, in the same order for every tool and grouped by capability; Pass and Fail come from published Results.

PassedFailedPublished, different test setNo published Result yet
ToolScenario results · 12 scenarios in 8 capabilitiesPassedFailedExplore
PyMuPDF4LLM
7 of 12 scenarios published · 4 passed · 3 failed
4of 7 graded3View tool →
Docling
6 of 12 scenarios published · 2 passed · 4 failed
2of 6 graded4View tool →
LiteParse
6 of 12 scenarios published · 3 passed · 3 failed
3of 6 graded3View tool →
MarkItDown
3 of 12 scenarios published · 1 passed · 2 failed
1of 3 graded2View tool →
6 more toolsin the rosterNo published Results yet for doc2mark · GPT-5.6 terra · Marker · MinerU · olmOCR · PaddleOCR-VL.Each tool gets its own row here once its first Result is published.

Capabilities & scenarios

12 scenarios grouped by 8 capabilities. Open a group to explore its scenarios in this benchmark.

Text Fidelity1 scenario

Whether ordinary digital text comes through complete, unchanged, and not invented in the Markdown output.

Capability in this benchmark → · Global definition →

  1. An ordinary digital text document1 tool with a published Result
Reading Order & Layout1 scenario

Whether the source page is read in the natural sequence, so text is not interleaved or reordered by layout.

Capability in this benchmark → · Global definition →

  1. A page laid out in multiple columns1 tool with a published Result
Heading & Section Structure2 scenarios

Whether headings and subheadings become real Markdown structure, with section hierarchy intact and footnotes kept attached outside the body flow.

Capability in this benchmark → · Global definition →

  1. A document with styled headings and subheadings3 tools with published Results
  2. Footnotes at the bottom of the page3 tools with published Results
Table Extraction2 scenarios

Whether tables keep their rows, columns, headers, and cell values as a table.

Capability in this benchmark → · Global definition →

  1. A simple, clearly formatted table3 tools with published Results
  2. A table that continues across a page breakNo published results
Figures & Charts2 scenarios

Whether figures and charts remain placed, referenced, and captioned or titled, with a text trace that still points back to the source.

Capability in this benchmark → · Global definition →

  1. A document with figures and captionsNo published results
  2. A document with a data chart3 tools with published Results
Scanned Document OCR2 scenarios

Whether image-only pages are turned into accurate text instead of being skipped or left unread.

Capability in this benchmark → · Global definition →

  1. A cleanly scanned document1 tool with a published Result
  2. A document mixing digital and scanned pages2 tools with published Results
Equations & Mathematical Notation1 scenario

Whether equations survive as math markup or a clear fallback instead of garbled prose.

Capability in this benchmark → · Global definition →

  1. A document containing mathematical equations3 tools with published Results
Code Extraction1 scenario

Whether code survives as a fenced block with line breaks and indentation intact.

Capability in this benchmark → · Global definition →

  1. A document containing a code block2 tools with published Results

Results overview

Current published evidence in this benchmark.

22Current published Results
10Scenarios with published Results
4Tools with published Results

Publication availability is separate from test coverage and unpublished research progress.

Explore scenarios →

How the benchmark works

A public summary of the evaluation method. The same defined scope and evidence standard apply to every tool assessed under this version.

Evaluation unit

One test case for one tool

Each verdict applies to one test case run against one tool.

Outcomes

Pass, fail, or not gradable

A result is pass, fail, or not gradable; not gradable is not a failure.

Consistency

Versioned scenarios and registered resources

Use the registered scenario versions and the registered resource versions for every run.

Evidence standard

Recorded stimulus, complete output, relevant references

Keep the recorded stimulus, the complete output, and the relevant registered references with the verdict.

Full benchmark methodology →

Resources and fixtures

The registered material and systems that create a consistent test environment for this benchmark.

Converting a complex PDF into clean Markdown with an open-source library — Benchmark definition | AI Demos