marker vs opendataloader-pdf
Datalab's 39k-star PDF-to-Markdown/JSON converter: a layout pipeline plus an optional LLM pass for tables, forms and equations, with chunk output and form-value extraction built in. — versus — Deterministic PDF parser for AI pipelines: #1 extraction accuracy (0.907) on its public bench, bounding boxes on every element, 0.015s/page — plus the first open PDF auto-tagging for accessibility.
Pick opendataloader-pdf when the corpus is born-digital and you want deterministic, model-free extraction with bounding boxes; marker when you accept model calls to recover tables, forms and math.
| marker | opendataloader-pdf | |
|---|---|---|
| Stars | 39k | 29k |
| Forks | 2.8k | 2.7k |
| Language | Python | Java |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | 17 days ago | today |
| Topics | ocr, rag | ocr, rag |
| Curated connections | 7 | 4 |
marker — the curator's take
The default answer when you need a lot of documents turned into clean Markdown on your own hardware: fast per page, tuned by people who do this for a living, and it can call Gemini/Claude/OpenAI-compatible/Ollama models only on the blocks that need help. Two caveats before you ship it: the code is Apache-2.0 but the model weights are OpenRAIL-M (free for research, personal use and companies under $5M funding/revenue), and on genuinely nasty input — scans, handwriting, dense multi-column tables — Datalab's own VLM chandra beats it. Born-digital corpus and no appetite for model calls? Use a deterministic parser instead.
opendataloader-pdf — the curator's take
Two products in one repo, both rare: a benchmark-topping deterministic parser (Markdown/JSON/HTML with bounding boxes, XY-Cut++ reading order, 0.015s/page, hybrid AI mode when you want it) and the first open-source auto-tagging to Tagged PDF — the accessibility path, built with the PDF Association and validated by veraPDF. Java core with Python/Node SDKs. NOT fully open at the edges: PDF/UA export and the accessibility studio are the enterprise add-on, and Java 11+ is a heavier runtime than the Rust competition. Benchmark caveat: the #1 score is on their own (public, reproducible) bench — verify on your documents.