olmOCR vs Paperless-AI
Short answer
olmOCR: Ai2's vision-language OCR that turns PDFs and scans into clean Markdown, including tables, equations and handwriting. Paperless-AI: AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). Both are in our Document processing category.
Choose olmOCR if you want: larger community (19.8k vs 6.0k GitHub stars) and simpler deploy (one container vs a multi-container stack).
Choose Paperless-AI if you want: no GPU server needed.
Paperless-AI publishes 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
olmOCR vs Paperless-AI side by side
| olmOCR | Paperless-AI | |
|---|---|---|
| Category | Document processing | Document processing |
| What it is | Ai2's vision-language OCR that turns PDFs and scans into clean Markdown, including tables, equations and handwriting. | AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). |
| License | Apache-2.0 | MIT |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use, modification and redistribution allowed; keep the license and notices. | Permissive. Internal and commercial use allowed; keep the copyright notice. |
| Status | Stale (no commit in 180+ days) | Stale (no commit in 180+ days) |
| GitHub stars | 19.8k | 6.0k |
| Last commit | Mar 25, 2026 | Mar 31, 2026 |
| Latest release | v0.4.27 | v3.0.9 |
| Minimum hardware | 30 GB disk | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Required for local inference: a recent NVIDIA GPU with at least 12 GB of GPU RAM (tested on RTX 4090, L40S, A100, H100). Without a GPU you can point it at a remote vLLM or OpenAI-compatible server. | Not required / not stated |
| Est. server cost | GPU server (not estimated) | Not estimated |
| Deploy method | Docker (GPU image with model included) | Docker |
| Known gotchas | 3 listed | 2 listed |
| Telemetry | Not documented | Not documented |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not documented | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Not documented |
| Details | Full olmOCR guide → | Full Paperless-AI guide → |
Key differences
- License: olmOCR: Apache-2.0 (Permissive). Paperless-AI: MIT (Permissive).
- GPU: olmOCR: needed for practical use. Paperless-AI: not required or not stated.
- Est. server cost: olmOCR: GPU server (not estimated). Paperless-AI: not estimated (no official RAM figure).
- Deploy: olmOCR: Docker (GPU image with model included) · single container. Paperless-AI: Docker · multi-container stack.
- GitHub stars: olmOCR: 19.8k. Paperless-AI: 6.0k.
- Last commit: olmOCR: Mar 25, 2026. Paperless-AI: Mar 31, 2026.
- Latest release: olmOCR: v0.4.27 (Mar 12, 2026). Paperless-AI: v3.0.9 (Nov 4, 2025).
Same for both: Category: Document processing; Official hardware: not published; Status: Stale (no commit in 180+ days).
olmOCR vs Paperless-AI: FAQ
olmOCR or Paperless-AI: which should a small business choose?
Choose olmOCR if you want: larger community (19.8k vs 6.0k GitHub stars) and simpler deploy (one container vs a multi-container stack). Choose Paperless-AI if you want: no GPU server needed. Paperless-AI publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, olmOCR or Paperless-AI?
olmOCR: GPU server (not estimated). 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 olmOCR and Paperless-AI need?
olmOCR: not published. Paperless-AI: not published. olmOCR needs a GPU for practical use.
What is the license difference between olmOCR and Paperless-AI?
olmOCR: Apache-2.0 (Permissive). Permissive. Internal and commercial use, modification and redistribution allowed; keep the license and notices. Paperless-AI: MIT (Permissive). Permissive. Internal and commercial use allowed; keep the copyright notice. This is a summary, not legal advice.
Is olmOCR or Paperless-AI more actively maintained?
olmOCR: Stale (no commit in 180+ days), last commit Mar 25, 2026. Paperless-AI: Stale (no commit in 180+ days), last commit Mar 31, 2026. GitHub data refreshed Nov 3, 2026.
Which is easier to deploy, olmOCR or Paperless-AI?
olmOCR installs via Docker (GPU image with model included) (single container); Paperless-AI via Docker (multi-container stack). olmOCR lists 3 known gotchas and Paperless-AI lists 2; see each app page.
Related
- olmOCR self-hosting guide · Paperless-AI self-hosting guide
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- All Paperless-AI alternatives, ranked
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- Docling Serve vs Paperless-AI
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- MinerU vs Paperless-AI
- OCRmyPDF vs olmOCR
- OCRmyPDF vs Paperless-AI
- olmOCR vs PaddleOCR
- olmOCR vs paperless-gpt
- olmOCR vs Paperless-ngx
- olmOCR vs Unstract
- PaddleOCR vs Paperless-AI
- Paperless-AI vs paperless-gpt
- Add a third app in the interactive comparison
Sources
- olmOCR GitHub repository: github.com/allenai/olmocr
- olmOCR documentation: github.com/allenai/olmocr#readme
- olmOCR license: github.com/allenai/olmocr/blob/main/LICENSE
- olmOCR hardware requirements: github.com/allenai/olmocr#python-installation
- olmOCR deploy instructions: github.com/allenai/olmocr#using-docker
- 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 2026-11-01): 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.