PaddleOCR vs Marker
Both are alternatives to AWS Textract. Here's how they stack up — verified facts, no spin.
Also searched as Marker vs PaddleOCR — same comparison, one verdict.
PaddleOCR
The strongest open OCR engine, and the best at non-Latin scripts.
PaddleOCR is a comprehensive OCR toolkit covering text detection, recognition, table extraction, layout analysis and key-value extraction, with support for around eighty languages. Its non-Latin script handling — Chinese, Japanese, Korean, Arabic — is clearly the best of the open options, and it ships lightweight mobile-scale models alongside the accurate server ones. Apache-2.0. If raw recognition accuracy on difficult scans is the constraint, this is the engine.
Marker
The best PDF-to-Markdown quality here — check the licence first.
Marker converts PDFs to Markdown with the highest fidelity of anything in this list: it handles equations, code blocks, tables and multi-column layouts, and optionally uses an LLM pass to improve difficult sections. For academic papers and technical documents the output quality is noticeably ahead. The caveat we would rather state than have you find in a licence review: Marker is GPL-3.0 with an additional revenue condition from its maintainer, so organisations above a revenue threshold need a commercial licence. Free for research and for smaller organisations, but not unconditionally.
Side by side
| PaddleOCR | Marker | |
|---|---|---|
| Sovereignty Score | 92 | 70 |
| Open source | Yes | No |
| Self-hostable | Yes | Yes |
| Local-first | Yes | Yes |
| License | Apache-2.0 | GPL-3.0 with commercial revenue condition |
| Pricing | Free, Apache-2.0. | Free below the maintainer's revenue threshold; a commercial licence is required above it. |
PaddleOCR edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
PaddleOCR
Strengths
- +Best-in-class open recognition accuracy on difficult scans
- +Around eighty languages, with excellent non-Latin coverage
- +Includes table, layout and key-value extraction
- +Lightweight models for edge and mobile deployment
Trade-offs
- −Built on the PaddlePaddle framework — an extra dependency to adopt
- −Documentation is stronger in Chinese than in English
- −Output needs more post-processing than Docling's Markdown
Marker
Strengths
- +Best PDF-to-Markdown fidelity of the options here
- +Handles equations, code blocks and complex tables well
- +Optional LLM pass for difficult pages
- +Runs entirely locally
Trade-offs
- −Not unconditionally open source — revenue-gated commercial terms
- −GPL-3.0 copyleft affects how you can distribute derived work
- −GPU strongly recommended for reasonable throughput
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Facts verified 2026-08-11. Licenses and pricing change — spotted something out of date? That's a correction we want.