OCRmyPDF vs Paperless-AI
Short answer
OCRmyPDF: Command-line tool and Docker image that adds a searchable OCR text layer to scanned PDFs, with a watched-folder service. Paperless-AI: AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). Both are in our Document processing category.
Choose OCRmyPDF if you want: an actively maintained project (Paperless-AI is stale), larger community (35.2k vs 6.0k GitHub stars) and simpler deploy (one container vs a multi-container stack).
Choose Paperless-AI if you want: fewer license conditions (Permissive vs Copyleft (GPL)).
OCRmyPDF and Paperless-AI publish no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
OCRmyPDF vs Paperless-AI side by side
| OCRmyPDF | Paperless-AI | |
|---|---|---|
| Category | Document processing | Document processing |
| What it is | Command-line tool and Docker image that adds a searchable OCR text layer to scanned PDFs, with a watched-folder service. | AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). |
| License | MPL-2.0 | MIT |
| License type | Copyleft (GPL) | Permissive |
| License conditions | Free for internal and commercial use. MPL-2.0 is file-level copyleft: if you distribute modified OCRmyPDF files, you must release those files' source under MPL-2.0. The demo web service is AGPL-3.0, and Ghostscript, which OCRmyPDF can use, is AGPL-licensed. | Permissive. Internal and commercial use allowed; keep the copyright notice. |
| Status | Active | Stale (no commit in 180+ days) |
| GitHub stars | 35.2k | 6.0k |
| Last commit | Oct 25, 2026 | Mar 31, 2026 |
| Latest release | v17.13.0 | v3.0.9 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | No. Tesseract runs on CPU; the optional EasyOCR plugin is the one that recommends a GPU. | Not required / not stated |
| Est. server cost | Not estimated | Not estimated |
| Deploy method | Docker (watched-folder service) | Docker |
| Known gotchas | 4 listed | 2 listed |
| Telemetry | Not documented | Not documented |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not applicable | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Not documented |
| Details | Full OCRmyPDF guide → | Full Paperless-AI guide → |
Key differences
- License: OCRmyPDF: MPL-2.0 (Copyleft (GPL)). Paperless-AI: MIT (Permissive).
- GPU: OCRmyPDF: optional / see notes. Paperless-AI: not required or not stated.
- Deploy: OCRmyPDF: Docker (watched-folder service) · single container. Paperless-AI: Docker · multi-container stack.
- Status: OCRmyPDF: Active. Paperless-AI: Stale (no commit in 180+ days).
- GitHub stars: OCRmyPDF: 35.2k. Paperless-AI: 6.0k.
- Last commit: OCRmyPDF: Oct 25, 2026. Paperless-AI: Mar 31, 2026.
- Latest release: OCRmyPDF: v17.13.0 (Sep 28, 2026). Paperless-AI: v3.0.9 (Nov 4, 2025).
Same for both: Category: Document processing; Official hardware: not published; Est. server cost: not estimated (no official RAM figure).
OCRmyPDF vs Paperless-AI: FAQ
OCRmyPDF or Paperless-AI: which should a small business choose?
Choose OCRmyPDF if you want: an actively maintained project (Paperless-AI is stale), larger community (35.2k vs 6.0k GitHub stars) and simpler deploy (one container vs a multi-container stack). Choose Paperless-AI if you want: fewer license conditions (Permissive vs Copyleft (GPL)). OCRmyPDF and Paperless-AI publish no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, OCRmyPDF or Paperless-AI?
OCRmyPDF: not estimated (no official RAM figure). Paperless-AI: not estimated (no official RAM figure). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do OCRmyPDF and Paperless-AI need?
OCRmyPDF: not published. Paperless-AI: not published.
What is the license difference between OCRmyPDF and Paperless-AI?
OCRmyPDF: MPL-2.0 (Copyleft (GPL)). Free for internal and commercial use. MPL-2.0 is file-level copyleft: if you distribute modified OCRmyPDF files, you must release those files' source under MPL-2.0. The demo web service is AGPL-3.0, and Ghostscript, which OCRmyPDF can use, is AGPL-licensed. Paperless-AI: MIT (Permissive). Permissive. Internal and commercial use allowed; keep the copyright notice. This is a summary, not legal advice.
Is OCRmyPDF or Paperless-AI more actively maintained?
OCRmyPDF: Active, last commit Oct 25, 2026. Paperless-AI: Stale (no commit in 180+ days), last commit Mar 31, 2026. GitHub data refreshed Nov 1, 2026.
Which is easier to deploy, OCRmyPDF or Paperless-AI?
OCRmyPDF installs via Docker (watched-folder service) (single container); Paperless-AI via Docker (multi-container stack). OCRmyPDF lists 4 known gotchas and Paperless-AI lists 2; see each app page.
Related
- OCRmyPDF self-hosting guide · Paperless-AI self-hosting guide
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- All Paperless-AI alternatives, ranked
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- PaddleOCR vs Paperless-AI
- Paperless-AI vs paperless-gpt
- Paperless-AI vs Paperless-ngx
- Paperless-AI vs Unstract
- Add a third app in the interactive comparison
Sources
- OCRmyPDF GitHub repository: github.com/ocrmypdf/OCRmyPDF
- OCRmyPDF documentation: ocrmypdf.readthedocs.io/en/latest/
- OCRmyPDF license: github.com/ocrmypdf/OCRmyPDF/blob/main/LICENSE
- OCRmyPDF hardware requirements: ocrmypdf.readthedocs.io/en/latest/performance.html
- OCRmyPDF deploy instructions: ocrmypdf.readthedocs.io/en/latest/batch.html
- Paperless-AI GitHub repository: github.com/clusterzx/paperless-ai
- Paperless-AI documentation: github.com/clusterzx/paperless-ai/wiki/2.-Installation
- Paperless-AI license: github.com/clusterzx/paperless-ai/blob/main/LICENSE
- Paperless-AI hardware requirements, Paperless-AI deploy instructions: github.com/clusterzx/paperless-ai#readme
- Hetzner Cloud pricing used for cost estimates (read 2026-10-25): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.