PhotoPrism vs LibrePhotos: Which Should You Self-Host?
Quick Verdict
PhotoPrism is the better choice. It’s more mature, faster, better documented, and has a larger community. LibrePhotos has some unique features (like a timeline view and auto-tagging with more detailed labels), but development has slowed and the project is less actively maintained. If you want to index and browse an existing photo library with AI features, PhotoPrism is the more reliable option.
Overview
PhotoPrism has been in development since 2018 and is the most established AI-powered photo indexer for self-hosting. It scans your existing photo library, classifies images using TensorFlow, detects faces, reads GPS data for map views, and provides a search interface that understands natural language queries. PhotoPrism uses MariaDB as its database and is available as a free AGPL edition with an optional paid “Essentials” tier.
LibrePhotos is a fork of the discontinued OwnPhotos project. It provides similar AI-powered photo classification using a machine learning backend, face detection, and a timeline-based browsing interface. LibrePhotos uses PostgreSQL and runs as multiple Docker containers (frontend, backend, PostgreSQL, Redis). Development has been less active in recent months.
Both aim to be smart photo library browsers — you point them at an existing directory of photos, and they index, classify, and organize everything automatically.
Feature Comparison
| Feature | PhotoPrism | LibrePhotos |
|---|---|---|
| Face recognition | Yes (built-in) | Yes (built-in) |
| Object classification | Yes (TensorFlow) | Yes (ML backend) |
| Smart search | Yes (CLIP-based natural language) | Yes (keyword-based) |
| Map view | Yes (OpenStreetMap) | Yes |
| Timeline view | Yes | Yes (stronger implementation) |
| Video support | Yes (playback + transcoding) | Basic (playback) |
| RAW file support | Yes (extensive: CR2, NEF, ARW, DNG, etc.) | Yes (common formats) |
| Multi-user support | Yes (roles, sharing) | Yes (users with separate libraries) |
| External library indexing | Yes (originals + import dirs) | Yes (scan directory) |
| Duplicate detection | Yes | Yes |
| Albums | Yes (manual + smart albums) | Yes (auto-generated + manual) |
| Sharing | Yes (link-based sharing) | Yes (link-based sharing) |
| OAuth/OIDC | Yes (Essentials tier) | No |
| Mobile app | No (responsive web UI) | No (web UI) |
| Auto-upload from phone | No | No |
| API | REST API | REST API |
| License | AGPL-3.0 (free) + paid Essentials | MIT (fully free) |
| Database | MariaDB | PostgreSQL |
Installation Complexity
PhotoPrism runs as two services: PhotoPrism itself and MariaDB. Configuration requires attention to detail — you need to set PHOTOPRISM_DATABASE_DRIVER: "mysql" (even though you’re using MariaDB), configure security options (security_opt: seccomp:unconfined), and ensure 4 GB of swap space for TensorFlow indexing. The number of environment variables is large, but well-documented.
LibrePhotos runs as four services: a backend (Django), a frontend (React), PostgreSQL, and Redis. The setup involves more containers and more environment variables to coordinate between them. The official docker-compose.yml is functional but the documentation is thinner than PhotoPrism’s.
Winner: PhotoPrism. Fewer services, better documentation, and more reliable first-run experience despite the configuration complexity.
Performance and Resource Usage
| Resource | PhotoPrism | LibrePhotos |
|---|---|---|
| RAM (idle) | ~400 MB | ~600 MB (4 containers) |
| RAM (indexing) | 2-4 GB (needs 4 GB swap) | 2-4 GB |
| CPU (idle) | Low | Low |
| CPU (indexing) | High (TensorFlow) | High (ML processing) |
| Disk (application) | ~3 GB (TF models + DB) | ~3 GB (ML models + DB) |
| Initial index (10K photos) | 20-45 minutes | 30-60 minutes |
| Startup time | 2-5 minutes (first run) | 2-5 minutes |
PhotoPrism is slightly lighter at idle (two containers vs four). Indexing performance is comparable, though PhotoPrism tends to be faster on the same hardware. Both require significant resources during initial indexing.
Winner: PhotoPrism (lighter at idle, faster indexing).
Community and Support
| Metric | PhotoPrism | LibrePhotos |
|---|---|---|
| GitHub stars | 35,000+ | 7,000+ |
| Release frequency | Monthly | Irregular (slowed) |
| Community | Active forum + Discord | GitHub issues + Discord |
| Documentation | Comprehensive (official docs site) | Adequate (GitHub wiki) |
| Development velocity | Steady | Slowed |
| Contributors | 200+ | 50+ |
| Long-term viability | Strong (funded by Essentials tier) | Uncertain |
PhotoPrism has a significantly larger community, better documentation, and a sustainable funding model through the paid Essentials tier. LibrePhotos’ development has slowed, which raises concerns about long-term maintenance.
Winner: PhotoPrism (larger community, better funding, more active development).
Use Cases
Choose PhotoPrism If…
- You have a large existing photo library you want to index and browse
- You want the most mature, well-documented AI photo indexer
- You need extensive RAW file support
- You want natural language search (“dog on beach”)
- You prefer a project with a clear sustainability model
- You need OAuth/OIDC support (Essentials tier)
- You value stability and documentation quality
Choose LibrePhotos If…
- You want a fully free solution (MIT license, no paid tier)
- You prefer timeline-based browsing as the primary view
- You want per-user library separation (each user has distinct photo directories)
- You’re comfortable with less documentation and community support
- You want to contribute to a smaller open-source project
Final Verdict
PhotoPrism is the clear winner. It’s more mature, better documented, has a larger community, and is actively maintained with a sustainable funding model. The AI classification and search capabilities are more advanced, RAW file support is more comprehensive, and the overall experience is more polished.
LibrePhotos is a decent project with an MIT license (more permissive than PhotoPrism’s AGPL), but slowing development and a smaller community make it harder to recommend for new deployments. If LibrePhotos’ development picks back up, this comparison could change — but today, PhotoPrism is the stronger choice.
For a full Google Photos replacement with mobile upload and native apps, skip both and use Immich. Both PhotoPrism and LibrePhotos are photo library browsers, not mobile-first photo management platforms.
FAQ
Can I run PhotoPrism and LibrePhotos together?
Yes, they use different databases and ports. You could test both against the same photo library (point both at the same read-only directory) and decide which you prefer before committing.
Which has better face recognition?
PhotoPrism’s face recognition is more reliable and produces fewer duplicate clusters. LibrePhotos’ face detection works but requires more manual merging of duplicate face groups.
Is PhotoPrism’s paid tier worth it?
The free AGPL tier covers most needs: indexing, search, face recognition, map view, sharing. The Essentials tier adds OAuth/OIDC, advanced search, and priority support. For personal use, the free tier is sufficient. For organizations needing SSO, it’s worth the cost.
Why not just use Immich?
Immich solves a different problem — it’s a Google Photos replacement with mobile auto-upload. PhotoPrism and LibrePhotos are for indexing existing photo collections. If you have 100K photos on a NAS and want a smart browsing interface, use PhotoPrism. If you want to upload photos from your phone and manage them, use Immich.
Is LibrePhotos still maintained?
As of early 2026, LibrePhotos receives occasional updates but development velocity has decreased significantly. The project is functional but new features are rare. Check the GitHub repository for the latest commit activity before deploying.
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