gptpdf vs markitdown
PDF and document-to-Markdown tools compared
gptpdf and markitdown convert files into Markdown for downstream use. gptpdf focuses on interpreting PDF pages with a vision-capable model, while markitdown handles a broader range of formats and emphasizes text and basic structure.
gptpdf: Convert PDFs into Markdown with Vision Models
gptpdf turns PDF pages into Markdown using a vision-capable model, aiming to preserve layouts such as tables, formulas, and figures. It suits developers who need an API-based PDF parsing component and can provide access to a compatible model.
markitdown: Convert Documents and Files to Markdown
MarkItDown converts documents and other files into Markdown for LLM and text-analysis workflows. It offers a Python library and command-line interface, with optional format-specific dependencies and plugins.
| gptpdf | markitdown | |
|---|---|---|
| Language | Python | Python |
| License | MIT | MIT |
| Stars | 3.6k | 188k |
| Forks | 261 | 13.9k |
| Last analyzed | Oct 3, 2026 | Oct 4, 2026 |
Key differences
- gptpdf focuses on PDFs; markitdown supports formats including office documents, HTML, images, audio, EPUB, ZIP, and YouTube URLs.
- gptpdf uses a compatible multimodal model API to interpret PDF pages; markitdown uses built-in converters and optional integrations, including Azure services and plugins.
- gptpdf provides a Python library; markitdown provides both a Python API and a command-line interface.
- gptpdf aims to retain visually complex PDF content such as formulas, tables, and figures; markitdown prioritizes readable text structure over high-fidelity visual reproduction.
- Both projects use Python and have an MIT license. Their listed popularity differs: gptpdf has 3.6k stars and markitdown has 188k.
- gptpdf's model-based parsing requires API access and may incur per-page costs; markitdown's Azure-based conversion requires an endpoint and makes billable API calls.
Choose gptpdf if you…
- need PDF parsing that uses model-based interpretation for visually complex pages.
- want to configure a compatible model API, prompts, and worker threads in a Python library.
- can provide model API access and accept its associated costs.
Choose markitdown if you…
- need to convert several document and media formats into Markdown.
- want both a Python API and a command-line tool, with optional format dependencies and plugins.
- prioritize text and basic structure for LLM or text-analysis workflows over visual fidelity.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.