Docling Serve vs Paperless-AI
Short answer
Docling Serve: Docling document conversion (PDF, Office, images to Markdown/JSON) as a self-hosted API with a demo UI. Paperless-AI: AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). Both are in our Document processing category.
Choose Docling Serve if you want: an actively maintained project (Paperless-AI is stale).
Choose Paperless-AI if you want: larger community (6.0k vs 1.9k GitHub stars).
Docling Serve 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
Docling Serve vs Paperless-AI side by side
| Docling Serve | Paperless-AI | |
|---|---|---|
| Category | Document processing | Document processing |
| What it is | Docling document conversion (PDF, Office, images to Markdown/JSON) as a self-hosted API with a demo UI. | AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). |
| License | MIT | MIT |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use allowed; keep the license notice. | Permissive. Internal and commercial use allowed; keep the copyright notice. |
| Status | Active | Stale (no commit in 180+ days) |
| GitHub stars | 1.9k | 6.0k |
| Last commit | Oct 27, 2026 | Mar 31, 2026 |
| Latest release | v1.38.2 | 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 | CPU-only image (docling-serve-cpu) is published; CUDA 12.8 and 13.0 images are available for NVIDIA GPUs, and an AMD ROCm image can be built locally. DOCLING_DEVICE picks cpu, cuda or mps, otherwise the best device is chosen. | Not required / not stated |
| Est. server cost | Not estimated | Not estimated |
| Deploy method | Container (Podman or Docker) | 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 documented | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Not documented |
| Details | Full Docling Serve guide → | Full Paperless-AI guide → |
Key differences
- GPU: Docling Serve: optional / see notes. Paperless-AI: not required or not stated.
- Deploy: Docling Serve: Container (Podman or Docker) · Container (Podman or Docker). Paperless-AI: Docker · multi-container stack.
- Status: Docling Serve: Active. Paperless-AI: Stale (no commit in 180+ days).
- GitHub stars: Docling Serve: 1.9k. Paperless-AI: 6.0k.
- Last commit: Docling Serve: Oct 27, 2026. Paperless-AI: Mar 31, 2026.
- Latest release: Docling Serve: v1.38.2 (Oct 27, 2026). Paperless-AI: v3.0.9 (Nov 4, 2025).
Same for both: Category: Document processing; License: MIT (Permissive); Official hardware: not published; Est. server cost: not estimated (no official RAM figure).
Docling Serve vs Paperless-AI: FAQ
Docling Serve or Paperless-AI: which should a small business choose?
Choose Docling Serve if you want: an actively maintained project (Paperless-AI is stale). Choose Paperless-AI if you want: larger community (6.0k vs 1.9k GitHub stars). Docling Serve and Paperless-AI publish no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, Docling Serve or Paperless-AI?
Docling Serve: 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 Docling Serve and Paperless-AI need?
Docling Serve: not published. Paperless-AI: not published.
What is the license difference between Docling Serve and Paperless-AI?
Docling Serve: MIT (Permissive). Permissive. Internal and commercial use allowed; keep the license notice. Paperless-AI: MIT (Permissive). Permissive. Internal and commercial use allowed; keep the copyright notice. This is a summary, not legal advice.
Is Docling Serve or Paperless-AI more actively maintained?
Docling Serve: Active, last commit Oct 27, 2026. Paperless-AI: Stale (no commit in 180+ days), last commit Mar 31, 2026. GitHub data refreshed Oct 28, 2026.
Which is easier to deploy, Docling Serve or Paperless-AI?
Docling Serve installs via Container (Podman or Docker) (Container (Podman or Docker)); Paperless-AI via Docker (multi-container stack). Docling Serve lists 4 known gotchas and Paperless-AI lists 2; see each app page.
Related
- Docling Serve self-hosting guide · Paperless-AI self-hosting guide
- All Docling Serve alternatives, ranked
- All Paperless-AI alternatives, ranked
- Docling Serve vs MinerU
- Docling Serve vs PaddleOCR
- Docling Serve vs paperless-gpt
- Docling Serve vs Unstract
- MinerU vs Paperless-AI
- PaddleOCR vs Paperless-AI
- Paperless-AI vs paperless-gpt
- Paperless-AI vs Unstract
- Add a third app in the interactive comparison
Sources
- Docling Serve GitHub repository: github.com/docling-project/docling-serve
- Docling Serve documentation: github.com/docling-project/docling-serve/blob/main/docs/README.md
- Docling Serve license: github.com/docling-project/docling-serve/blob/main/LICENSE
- Docling Serve hardware requirements: github.com/docling-project/docling-serve#container-images
- Docling Serve deploy instructions: github.com/docling-project/docling-serve#getting-started
- 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.