AFFiNE vs PrivateGPT
Short answer
AFFiNE: Notion- and Miro-style workspace (docs, whiteboards, databases) with built-in AI, self-hostable with Docker. PrivateGPT: API-first private document Q&A that sits on top of your own LLM server. Both are in our Knowledge base & RAG category.
Choose PrivateGPT if you want: fewer license conditions (Permissive vs Open core).
PrivateGPT 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
AFFiNE vs PrivateGPT side by side
| AFFiNE | PrivateGPT | |
|---|---|---|
| Category | Knowledge base & RAG | Knowledge base & RAG |
| What it is | Notion- and Miro-style workspace (docs, whiteboards, databases) with built-in AI, self-hostable with Docker. | API-first private document Q&A that sits on top of your own LLM server. |
| License | MIT (Community Edition) with Enterprise Edition license for server code | Apache-2.0 |
| License type | Open core | Permissive |
| License conditions | The README says the Community Edition is free to self-host under the MIT license. The server code under packages/backend carries an AFFiNE Enterprise Edition license that applies to parts not distributed as Community Edition. Self-hosted workspaces get up to 10 seats; more seats need a paid Team Plan or Installable License. | Permissive. Internal and commercial use allowed; keep license and notices. |
| Status | Active | Active |
| GitHub stars | 74.0k | 57.6k |
| Last commit | Oct 27, 2026 | Oct 26, 2026 |
| Latest release | v0.27.4 | v1.0.1 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | 4 vCPU · 2 GB RAM | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Not required / not stated | Not required / not stated |
| Est. server cost | from €35.99/mo | Not estimated |
| Deploy method | Docker Compose (official images) | uv (Python) or Docker |
| Known gotchas | 4 listed | 2 listed |
| Telemetry | Not documented | Not documented |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Free with limits (OIDC free) | Paid / enterprise only (LDAP paid) |
| Audit log | Not documented | Paid / enterprise only |
| RBAC | Not documented | Paid / enterprise only |
| Details | Full AFFiNE guide → | Full PrivateGPT guide → |
Key differences
- License: AFFiNE: MIT (Community Edition) with Enterprise Edition license for server code (Open core). PrivateGPT: Apache-2.0 (Permissive).
- Official hardware: AFFiNE: recommended 4 vCPU · 2 GB RAM (no separate minimum published). PrivateGPT: not published.
- Est. server cost: AFFiNE: from €35.99/mo. PrivateGPT: not estimated (no official RAM figure).
- Deploy: AFFiNE: Docker Compose (official images) · multi-container stack. PrivateGPT: uv (Python) or Docker · uv (Python) or Docker.
- GitHub stars: AFFiNE: 74.0k. PrivateGPT: 57.6k.
- Last commit: AFFiNE: Oct 27, 2026. PrivateGPT: Oct 26, 2026.
- Latest release: AFFiNE: v0.27.4 (Aug 18, 2026). PrivateGPT: v1.0.1 (Jun 18, 2026).
Same for both: Category: Knowledge base & RAG; GPU: not required or not stated; Status: Active.
AFFiNE vs PrivateGPT: FAQ
AFFiNE or PrivateGPT: which should a small business choose?
Choose PrivateGPT if you want: fewer license conditions (Permissive vs Open core). PrivateGPT publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, AFFiNE or PrivateGPT?
AFFiNE: from €35.99/mo. PrivateGPT: 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 AFFiNE and PrivateGPT need?
AFFiNE: recommended 4 vCPU · 2 GB RAM (no separate minimum published). PrivateGPT: not published.
What is the license difference between AFFiNE and PrivateGPT?
AFFiNE: MIT (Community Edition) with Enterprise Edition license for server code (Open core). The README says the Community Edition is free to self-host under the MIT license. The server code under packages/backend carries an AFFiNE Enterprise Edition license that applies to parts not distributed as Community Edition. Self-hosted workspaces get up to 10 seats; more seats need a paid Team Plan or Installable License. PrivateGPT: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed; keep license and notices. This is a summary, not legal advice.
Is AFFiNE or PrivateGPT more actively maintained?
AFFiNE: Active, last commit Oct 27, 2026. PrivateGPT: Active, last commit Oct 26, 2026. GitHub data refreshed Oct 29, 2026.
Which is easier to deploy, AFFiNE or PrivateGPT?
AFFiNE installs via Docker Compose (official images) (multi-container stack); PrivateGPT via uv (Python) or Docker (uv (Python) or Docker). AFFiNE lists 4 known gotchas and PrivateGPT lists 2; see each app page.
Related
- AFFiNE self-hosting guide · PrivateGPT self-hosting guide
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- All PrivateGPT alternatives, ranked
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- AFFiNE vs PipesHub
- AFFiNE vs RAGFlow
- AnythingLLM vs PrivateGPT
- DocsGPT vs PrivateGPT
- FastGPT vs PrivateGPT
- Add a third app in the interactive comparison
Sources
- AFFiNE GitHub repository: github.com/toeverything/AFFiNE
- AFFiNE documentation: docs.affine.pro/self-host-affine
- AFFiNE license: github.com/toeverything/AFFiNE/blob/canary/LICENSE
- AFFiNE hardware requirements: docs.affine.pro/self-host-affine/install/requirements
- AFFiNE deploy instructions: docs.affine.pro/self-host-affine/install/docker-compose-recommended
- PrivateGPT GitHub repository: github.com/zylon-ai/private-gpt
- PrivateGPT documentation, PrivateGPT hardware requirements: docs.privategpt.dev/getting-started/quickstart
- PrivateGPT license: github.com/zylon-ai/private-gpt/blob/main/LICENSE
- PrivateGPT deploy instructions: github.com/zylon-ai/private-gpt#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.