Question 1

OCRmyPDF or paperless-gpt: which should a small business choose?

Accepted Answer

Choose OCRmyPDF if you want: larger community (35.2k vs 2.8k GitHub stars) and simpler deploy (one container vs a multi-container stack). Choose paperless-gpt if you want: fewer license conditions (Permissive vs Copyleft (GPL)). OCRmyPDF and paperless-gpt publish no official RAM figure, so we cannot compare hosting cost directly.

Question 2

Which is cheaper to self-host, OCRmyPDF or paperless-gpt?

Accepted Answer

OCRmyPDF: not estimated (no official RAM figure). paperless-gpt: 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.

Question 3

How much hardware do OCRmyPDF and paperless-gpt need?

Accepted Answer

OCRmyPDF: not published. paperless-gpt: not published.

Question 4

What is the license difference between OCRmyPDF and paperless-gpt?

Accepted Answer

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-gpt: MIT (Permissive). Permissive. Internal and commercial use allowed; keep the license notice. This is a summary, not legal advice.

Question 5

Is OCRmyPDF or paperless-gpt more actively maintained?

Accepted Answer

OCRmyPDF: Active, last commit Oct 25, 2026. paperless-gpt: Active, last commit Oct 16, 2026. GitHub data refreshed Nov 1, 2026.

Question 6

Which is easier to deploy, OCRmyPDF or paperless-gpt?

Accepted Answer

OCRmyPDF installs via Docker (watched-folder service) (single container); paperless-gpt via Docker Compose (multi-container stack). OCRmyPDF lists 4 known gotchas and paperless-gpt lists 3; see each app page.

	OCRmyPDF	paperless-gpt
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.	LLM add-on for paperless-ngx that does better OCR and writes titles, tags and correspondents.
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 license notice.
Status	Active	Active
GitHub stars	35.2k	2.8k
Last commit	Oct 25, 2026	Oct 16, 2026
Latest release	v17.13.0	v0.31.0
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 needed for the app itself. A GPU only matters if you run the LLM locally (for example with Ollama).
Est. server cost	Not estimated	Not estimated
Deploy method	Docker (watched-folder service)	Docker Compose
Known gotchas	4 listed	3 listed
Telemetry	Not documented	Not documented
Calls home by default	Not documented	Not documented
SSO (OIDC / SAML / LDAP)	Not applicable	Not supported (OIDC not supported · SAML not supported · LDAP not supported)
Audit log	Not documented	Not documented
RBAC	Not documented	No
Details	Full OCRmyPDF guide →	Full paperless-gpt guide →

OCRmyPDF vs paperless-gpt

Short answer