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· 8 min read · MDisBetter

MDisBetter vs Marker: Hosted vs Self-Hosted PDF to Markdown

Marker is a well-known open-source PDF-to-Markdown library that runs locally on your own hardware. MDisBetter is a hosted web converter. The clearest difference between them is not a score: it is whether you want to operate the conversion infrastructure yourself. This page covers that operational difference, the cases where each one fits, and how to compare output quality on your own documents.

How to compare output quality yourself

Output quality depends on your documents, so test both tools on a sample of the PDFs you actually handle, for example academic papers, reports and scanned documents. Run both at default settings and score each output on:

Scoring each dimension from 0 to 10 per document makes differences visible while keeping every output small enough to inspect by hand. How to benchmark PDF to Markdown converters walks through the full method.

Where Marker fits best

Equation-heavy documents

Marker uses a specialized math model trained specifically on equation recognition. If your documents are dense with math (physics papers, theoretical CS), give equations a heavy weight when you compare the two tools on your own files.

Steady volume on your own hardware

Once Marker's environment and model weights are in place on a GPU you already own, each extra document costs you only compute. MDisBetter needs nothing installed, which matters most when documents arrive occasionally rather than in a steady stream.

Air-gapped data

Marker runs entirely on your hardware. No data ever leaves your network. For workloads where data residency is a hard requirement (classified material, certain regulated industries), Marker is the only one of the two that can work at all.

Where MDisBetter fits best

No infrastructure to run

MDisBetter is a web tool: drop a PDF in the browser, convert, and download the .md file. Heading levels are preserved and tables are rebuilt as Markdown tables. There is no Python environment, GPU driver or model download to manage, and updates reach you without any action on your side.

Operational comparison

This is where the two tools really diverge:

DimensionMDisBetterMarker
SetupA free account and a browserPython environment, GPU drivers, model download
Ongoing maintenanceNone on your sideModel updates, dependency upgrades
Compute costCredits per conversion, paid plans for more volumeYour GPU time plus ops time

Which one costs less depends on your volume: price MDisBetter's plans against your GPU time and engineering hours at your real monthly page count. Self-hosting Marker tends to pay off at high volume, and only if you have the engineering capacity to operate it.

Recommendation

Pick Marker when:

Pick MDisBetter when:

Both are good products, and the choice is mostly about your operational profile. Before you commit, run a few of your own documents through both.

For the side-by-side feature table, see /compare/mdisbetter-vs-marker.

Frequently asked questions

Can I use both: Marker for sensitive data, MDisBetter for everything else?
Yes. Run Marker locally for the documents that can't leave your network; use MDisBetter for the rest. Your downstream code consumes Markdown either way and doesn't care which engine produced it.
How often does Marker get updated vs MDisBetter?
Marker: new releases ship on GitHub and you upgrade manually. MDisBetter: hosted, so improvements reach you without any upgrade on your side. Different operational implications.
Is Marker really free?
The code is Apache 2.0 licensed. The model weights come under a separate license: free for research, personal use and startups below a funding and revenue threshold, with a paid license from Datalab for larger commercial use (the Marker README gives the details). Beyond licensing, your cost is the compute to run it and the engineering time to operate it.