MarkItDown vs Pandoc vs Markdownify: Which Converter for What?

If you regularly convert documents to Markdown, you have probably used one of these three tools: MarkItDown, Pandoc, or Markdownify. All three solve similar problems but are built for different use cases. This guide shows you which tool is right when, based on real characteristics rather than marketing promises.

Transparency note: This website is a browser frontend for the Microsoft MarkItDown library. The comparison still tries to be fair and explicitly names weaknesses of MarkItDown. If Pandoc fits your case better, you should use Pandoc.

The three tools at a glance

MarkItDown is an open-source library from Microsoft, originally developed to prepare documents for LLM inputs. It can convert PDF, DOCX, XLSX, PPTX, images, HTML, CSV, and more to Markdown. Runs as a Python library or, as on markitdown.de, directly in the browser via WebAssembly.

Pandoc is the veteran among converters, developed by John MacFarlane since 2006. Often called the "Swiss army knife of document conversion." Can convert between more than 40 formats, including LaTeX, ePub, DocBook, MediaWiki, and many more. Runs as a command-line tool or as a library.

Markdownify is a leaner solution, focused on HTML-to-Markdown conversion. Exists in several variants as Python library, JavaScript library, or simple web pages. Does one thing, but does it well.

Comparison table

When MarkItDown is the right choice

MarkItDown is optimized for the case that likely brought you here: you want to turn Office documents and PDFs into LLM-ready Markdown.

Strengths in practice:

• Broad format coverage out of the box, without configuration. You throw in a PDF, DOCX, XLSX, or image and get Markdown out.
• OCR is integrated. Scanned PDFs are automatically detected and text is extracted. Pandoc cannot do that.
• Browser variant without installation. On MarkItDown in the browser, you convert without setup, without Python, without command line. For non-developers, this is often the deciding advantage.
• Table detection in PDFs works solidly. Pandoc often loses structure here.
• Excel sheets become Markdown tables. With Pandoc, this only works via CSV detours, with Markdownify not at all.

Weaknesses you should know:

• No LaTeX support. If you want to convert scientific papers with formulas, Pandoc is better.
• Configurability is limited. You get the standard Markdown, but cannot define your own transformation rules.
• For very complex layouts (multi-column PDFs with tables, embedded diagrams), MarkItDown hits limits. Here it sometimes loses reading order.

When Pandoc is the right choice

Pandoc is the tool for professionals who treat document conversion as a serious discipline. It can do more than MarkItDown but also demands more from you.

Strengths in practice:

• Over 40 formats, including academic standards like LaTeX, DocBook, JATS, BibTeX. If you work in academia, there is no way around Pandoc.
• Extremely configurable. You can write your own Lua filters, define templates, control every transformation.
• Very stable and mature since 2006. Pandoc has seen almost every edge case in 20 years.
• Bidirectional. Pandoc can convert not only to Markdown but also from Markdown to other formats (PDF via LaTeX, HTML, ePub, Word, etc.).

Weaknesses you should know:

• Steep learning curve. The command-line syntax is powerful but not intuitive. You will read the docs multiple times.
• No native OCR. Scanned PDFs you have to push through an OCR tool first before Pandoc can process them.
• PDF conversion is not Pandoc's strength. Pandoc can do PDF more as output, not as input.
• Browser use practically impossible. Pandoc is primarily a command-line tool.

When Markdownify is the right choice

Markdownify is the specialist for one single task: HTML to Markdown.

Strengths in practice:

• Extremely focused and stable. Does HTML-to-Markdown conversion well and quickly.
• Very lightweight. The Python library is small, the JS variant likewise. Loads fast, runs everywhere.
• Easy to integrate. If you build a web app that wants to store user-generated HTML as Markdown, Markdownify is the obvious choice.

Weaknesses you should know:

• HTML only. No PDFs, no Office formats, no images. Therefore not sufficient for most LLM use cases.
• Configurability limited. You can adjust basic rules but cannot write deep transformations.
• No table optimization. Complex HTML tables are sometimes flattened.

Decision cheatsheet

Three quick questions that lead you to the right choice:

Question one, what are your typical source documents?
PDF, DOCX, XLSX, PPTX, images → MarkItDown
LaTeX, ePub, DocBook, scientific formats → Pandoc
HTML snippets, web content → Markdownify

Question two, where do you work?
Browser, no installation → MarkItDown (markitdown.de)
Command line, with full control → Pandoc
In an app, as integrated library → Markdownify (for HTML) or MarkItDown (for Office)

Question three, how critical is layout preservation?
Standard conversion is enough → MarkItDown
Pixel-precise control needed → Pandoc with custom Lua filters
Just plain Markdown without frills → Markdownify

A concrete example with identical input

To make the difference tangible, here is a simple example: a small HTML file with a heading, a list, and a table.

<h1>Quarterly Report</h1>
<p>Revenue in <strong>Q4</strong> rose by <em>12 percent</em>.</p>
<ul>
  <li>Product A: 4.2 million EUR</li>
  <li>Product B: 2.1 million EUR</li>
</ul>

MarkItDown output:

# Quarterly Report

Revenue in **Q4** rose by *12 percent*.

- Product A: 4.2 million EUR
- Product B: 2.1 million EUR

Pandoc output:

# Quarterly Report

Revenue in **Q4** rose by *12 percent*.

-   Product A: 4.2 million EUR
-   Product B: 2.1 million EUR

Markdownify output:

Quarterly Report
================

Revenue in **Q4** rose by _12 percent_.

* Product A: 4.2 million EUR
* Product B: 2.1 million EUR

The outputs differ only in nuances: Pandoc uses three spaces after the bullet, Markdownify uses Setext-style headings with underline, MarkItDown stays with the compact standard form. For LLMs, all three outputs are equivalent because modern models understand all variants.

The difference grows when you have more complex inputs: PDFs with tables, Excel sheets, scanned documents. This is where each tool shows what it was built for.

Common misconceptions

Misconception one, "Pandoc is always better because it's older." Older does not mean better for your use case. Pandoc is excellent for academic workflows, but for Office-to-LLM pipelines it was never optimized.

Misconception two, "MarkItDown is just the Microsoft library." Partly true. The library is open source and can be used standalone, or through frontends like MarkItDown in the browser. You don't have to choose.

Misconception three, "Markdownify is enough for everything." If you really only convert HTML, yes. But once PDFs or Office formats come into play, you need a different tool.

Misconception four, "Browser conversion is always worse than command line." Not anymore. WebAssembly has largely neutralized the performance gap. The browser variant of MarkItDown uses the same library as the Python variant.

Conclusion and recommendation

If you regularly convert Office documents, PDFs, and images for LLM inputs, MarkItDown is the simplest and most complete solution. If you work in academia or need highly complex transformations, Pandoc is the right tool, even if the learning takes time. If you need a lean HTML-to-Markdown solution, Markdownify is sufficient.

In practice, many power users use two tools in parallel: MarkItDown in the browser for quick ad-hoc conversions, Pandoc for pipeline automation in the backend. They don't exclude each other, they complement each other.

Read more

• Use MarkItDown directly for instant conversion in the browser
• Convert PDF to Markdown for PDF-specific peculiarities
• What is Markdown?, if you haven't read the basics guide yet
• Feeding Claude Projects with documents, for the step after conversion