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Marker supports PDF, image, PPTX, DOCX, XLSX, HTML, and EPUB files. The README notes that non-PDF document support requires installing additional dependencies with marker-pdf[full].
Marker can output markdown, HTML, JSON, and chunks. Markdown includes image links, formatted tables, LaTeX equations, fenced code blocks, and footnote superscripts; JSON exposes a tree-like block structure; chunks flatten top-level blocks for easier RAG indexing.
LLM use is optional. With --use_llm, Marker can improve accuracy for cases such as table merging across pages, inline math, table formatting, and extracting values from forms. The README lists Gemini, Google Vertex, Ollama, Claude, OpenAI-compatible endpoints, and Azure OpenAI as supported LLM services.
Yes. Marker can run locally through CLI commands such as marker_single and marker, through Python APIs, through a Streamlit GUI, or through a lightweight FastAPI server. It can run on GPU, CPU, or Apple MPS, with Torch device detection and override options.
Not for all commercial situations. The repository states that the code is GPL-3.0 and the model weights use a modified AI Pubs Open Rail-M license that is free for research, personal use, and startups under $2M funding or revenue. Broader commercial licensing or removing GPL requirements requires Datalab’s commercial licensing.
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Last verified March 2026