Marker vs MarkItDown: Which PDF-to-Markdown Tool Should You Use?

Marker vs MarkItDown: Which PDF-to-Markdown Tool Should You Use?

Both Marker and Microsoft's MarkItDown are popular open-source ways to turn documents into Markdown for LLMs — but they are built for different jobs. Marker is a deep, ML-powered PDF converter; MarkItDown is a light, broad, any-file converter. This post shows where each one wins.

Want the output without installing anything? file2markdown converts the same files through a browser or REST API with no Python setup.

The Quick Answer

Use Marker when PDFs are your priority and quality matters most — complex layouts, math, tables, and scanned pages where accurate Markdown is worth the heavier setup.

Use MarkItDown when you need a fast, lightweight converter across many file types (Office, images, audio, EPUB, HTML) and your documents are fairly standard.

Use file2markdown when you want hosted conversion for PDF, PPTX, XLSX, and images without managing GPUs or dependencies.

What Each Tool Is

Marker is an open-source pipeline focused on converting PDFs (plus some other formats) to high-quality Markdown. It uses ML models for layout detection, OCR, table parsing, and even equations, and benefits heavily from a GPU. It is the go-to when fidelity on hard PDFs matters more than install simplicity.

MarkItDown (by Microsoft) is a lightweight converter that wraps existing parsers behind one convert() call and returns LLM-friendly Markdown. It trades deep PDF fidelity for breadth and speed, supporting many file types with a tiny install.

Head-to-Head Comparison

	Marker	MarkItDown
Focus	High-quality PDF conversion	Broad, lightweight conversion
Format support	PDF-first (+ some others)	PDF, Office, images, audio, EPUB, HTML
Table & math handling	Strong (ML models)	Basic
OCR / scanned PDFs	Yes (built-in)	Limited
Hardware	GPU recommended	Runs anywhere
Install footprint	Large (models)	Small
Speed	Slower, higher quality	Fast
Best fit	Accuracy on hard PDFs	Many files, simple docs

Installing and Using Each

Marker

pip install marker-pdf

from marker.converters.pdf import PdfConverter
from marker.models import create_model_dict

converter = PdfConverter(artifact_dict=create_model_dict())
rendered = converter("report.pdf")
print(rendered.markdown)

Expect model downloads on first run and much better throughput on a GPU. The payoff is clean Markdown from documents that trip up lighter tools.

MarkItDown

pip install markitdown

from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("report.pdf")
print(result.text_content)

One call, one Markdown string, runs on any machine — ideal when documents are straightforward and you value speed.

When to Reach for file2markdown Instead

Marker wants a GPU and model management; MarkItDown is light but shallow on hard PDFs. If you want Marker-grade results without owning the infrastructure — or you are calling from outside Python — file2markdown gives you:

• Hosted PDF and image conversion with server-side OCR
• A REST API for batch and automated pipelines
• No GPU, no model downloads, no dependency juggling

Bottom Line

Reach for Marker when PDF quality is the priority and you can run models on a GPU. Reach for MarkItDown when you need a fast, broad converter for everyday files. And when you want strong results with none of the setup, file2markdown handles it as a hosted service.