Open WebUI vs LibreChat vs Jan
The Self-Hosted AI Chat Landscape
ChatGPT costs $20-200/month per user. But the technology driving it — large language models — can be run locally or on your own server. Three tools have emerged as the leading self-hosted interfaces: Open WebUI, LibreChat, and Jan.
All three are free, open source, and actively developed. All three connect to local models via Ollama or remote models via API. The differences are in architecture, feature set, target audience, and deployment complexity.
This comparison will help you pick the right one.
TL;DR
- Open WebUI: Best overall for teams deploying Ollama locally. Massive feature set, largest community (124K+ stars), best integration with the Ollama ecosystem.
- LibreChat: Best for organizations using multiple AI providers simultaneously. Deepest multi-provider support, enterprise auth, agent workflows.
- Jan: Best for individuals who want completely offline, desktop-native AI. No server, no Docker, no internet required.
Quick Comparison
| Feature | Open WebUI | LibreChat | Jan |
|---|---|---|---|
| GitHub Stars | 124K+ | 33K+ | 25K+ |
| Architecture | Web app + backend | Web app + backend | Desktop app |
| Deployment | Docker (2 services) | Docker (3+ services) | Direct install |
| Offline capable | Yes (with Ollama) | Yes (with Ollama) | Fully offline |
| Multi-user | Yes | Yes | No |
| Multi-provider | Good | Excellent | Good |
| RAG (doc chat) | Built-in | Built-in | Limited |
| Agents | Yes | Yes (advanced) | Basic |
| MCP support | Yes | Yes | Yes |
| Mobile | Web (PWA) | Web (PWA) | iOS/Android |
| License | MIT | MIT | AGPL-3.0 |
Open WebUI — Best for Teams Using Ollama
Open WebUI is the default choice when you're already running Ollama. With 124K+ GitHub stars and 10M+ Docker pulls, it's the most widely adopted self-hosted AI chat interface by a significant margin.
Architecture
Open WebUI runs as a web application backed by a Python/FastAPI server. It talks directly to Ollama for local models and supports any OpenAI-compatible API for cloud models.
services:
ollama:
image: ollama/ollama
volumes:
- ollama:/root/.ollama
open-webui:
image: ghcr.io/open-webui/open-webui:main
ports:
- "3000:8080"
environment:
- OLLAMA_BASE_URL=http://ollama:11434
Two services. Running in minutes.
Features
Model management: Pull, delete, and switch between Ollama models from the UI. No command line required after initial setup.
RAG (Retrieval-Augmented Generation): Upload PDFs, documents, or entire websites and chat with them using any loaded model. The RAG pipeline is built into Open WebUI — no external service needed.
Pipelines: A powerful extension system that lets you build custom processing chains — pre/post-process messages, route to different models, add tools.
Web search: Integrate DuckDuckGo, Google, or SearXNG for real-time web search in conversations.
Multi-modal: Image input (vision models), image generation (Automatic1111/ComfyUI integration), voice input/output.
Admin panel: User management, model access controls, usage statistics, rate limiting.
Tools and agents: Function calling, code execution, web browsing agents.
Who It's Best For
Open WebUI excels when you have a team that needs managed access to local models. The admin panel, user roles, and model access controls make it practical for small teams (5-50 people) to share a single Ollama server with appropriate permissions.
Limitations
- Feature-rich to the point of being overwhelming for new users
- RAG quality depends heavily on the embedding model configured
- Some advanced features (pipelines, custom tools) have a learning curve
- Documentation can lag behind feature releases
LibreChat — Best for Multi-Provider Organizations
LibreChat takes the platform approach: one unified interface for every AI provider your team uses. OpenAI, Anthropic, Google, Groq, AWS Bedrock, Azure OpenAI, local Ollama models — all accessible from the same chat interface with the same conversation history.
Architecture
LibreChat requires more services than Open WebUI:
services:
librechat:
image: ghcr.io/danny-avila/librechat
ports:
- "3080:3080"
mongodb:
image: mongo
volumes:
- mongo:/data/db
meilisearch:
image: getmeili/meilisearch
# For conversation search
rag_api:
image: ghcr.io/danny-avila/librechat-rag-api-dev
# Optional RAG service
Three to four services for full functionality. More setup, but the architecture supports larger deployments.
Features
Multi-provider in one interface: Switch between Claude 3.5, GPT-4o, Gemini, Mistral, DeepSeek, and local Llama in the same conversation thread. Compare responses from different models.
Agent system: Build agents with tool access — web search, code interpreter, file analysis. Agents persist and can be shared across your team.
MCP support: Full Model Context Protocol support for connecting external tool servers.
Enterprise auth: SSO via OIDC, OAuth2, SAML. Integrates with Google Workspace, Azure AD, Okta, GitHub, and Discord.
Conversation management: Search, tag, and organize conversations. Fork conversations to explore different directions.
Presets: Save model configurations as presets — specific models with specific system prompts and parameters for recurring tasks.
LibreChat got a Harvard partnership for digital accessibility, and it's the only tool on this list that has been used in formal accessibility research.
Who It's Best For
LibreChat fits organizations that:
- Use multiple AI providers simultaneously
- Need SSO/enterprise auth integration
- Want advanced agent workflows
- Have larger teams (20+ users) with varying AI provider preferences
Limitations
- More complex deployment than Open WebUI
- Requires MongoDB (adds operational overhead)
- Less integrated with Ollama's model management vs Open WebUI
- The multi-provider focus means the Ollama experience is less seamless
Jan — Best for Offline Individual Use
Jan operates on a completely different philosophy: your AI should work without the internet, without a server, and without any cloud dependency. Jan is a native desktop application that runs models entirely on your local machine.
Architecture
Jan is an Electron-based desktop app for macOS, Windows, and Linux. There's no server to manage, no Docker, no database. Install the app, download a model, start chatting.
For teams, Jan Server is a separate product that adds multi-user support, but the core desktop app is for individuals.
Features
Full offline operation: Once a model is downloaded, Jan works completely air-gapped. No network connection required.
Local API server: Jan exposes an OpenAI-compatible API at localhost:1337. Other applications can use Jan as their model backend.
Multiple engine support:
- llama.cpp for CPU and consumer GPU inference
- TensorRT-LLM for NVIDIA GPU acceleration
- Remote API connections (OpenAI, Anthropic, Groq) when you want cloud models
Model library: Browse and download models from Hugging Face directly in the Jan interface. One click to download and run.
Cross-platform: macOS (Apple Silicon and Intel), Windows, Linux. Native performance on Apple Silicon — M1/M2/M3 Macs run Llama 3.2 at 50+ tokens/second.
Jan Server (Enterprise)
Jan Server adds team features:
- Multi-tenant architecture
- Performance monitoring
- Health checks
- Centralized model management
Jan Server is a paid product — pricing is separate from the free desktop app.
Who It's Best For
Jan is ideal for:
- Individual developers who want completely private, offline AI
- Security-conscious professionals working with sensitive code/data
- Air-gapped environments where cloud AI is prohibited
- Apple Silicon Mac users who want maximum performance from local models
Limitations
- No built-in multi-user support in the free desktop version
- No shared conversation history across devices (without Jan Server)
- Limited RAG capabilities compared to Open WebUI or LibreChat
- Team collaboration requires Jan Server (paid)
Side-by-Side: Deployment Complexity
| Aspect | Open WebUI | LibreChat | Jan |
|---|---|---|---|
| Services required | 2 (Ollama + Open WebUI) | 3-4 (app + MongoDB + Meilisearch) | 0 (desktop app) |
| Setup time | 5-10 minutes | 20-30 minutes | 5 minutes |
| Reverse proxy needed | Yes (for team access) | Yes (for team access) | No |
| SSL configuration | Yes (for team access) | Yes (for team access) | No |
| Model management | Via UI (Ollama) | Via settings | Via UI |
| Updates | Docker pull | Docker pull | App update |
Side-by-Side: AI Provider Support
| Provider | Open WebUI | LibreChat | Jan |
|---|---|---|---|
| Ollama (local) | Native integration | Supported | Native integration |
| OpenAI | Yes | Yes | Yes |
| Anthropic (Claude) | Yes | Yes | Yes |
| Google Gemini | Yes | Yes | Yes |
| Groq | Yes | Yes | Yes |
| AWS Bedrock | No | Yes | No |
| Azure OpenAI | Limited | Yes | No |
| Custom API | Yes | Yes | Yes |
Which One Should You Choose?
Choose Open WebUI if:
- You're running Ollama and want the best integration
- You need a team-accessible web interface
- You want the largest community and most active development
- RAG (chat with documents) is important to you
- You want a polished admin interface for managing users
Choose LibreChat if:
- Your team uses multiple AI providers (some tasks on Claude, some on GPT-4o, some local)
- You need enterprise SSO (OIDC, SAML, Azure AD)
- You want advanced agent workflows with persistent tool-using agents
- You're deploying for 20+ users with complex access control requirements
Choose Jan if:
- You're an individual user who wants completely offline AI
- You're on Apple Silicon and want maximum local model performance
- Your work environment requires air-gapped AI (security/compliance)
- You don't want to manage any server infrastructure
Self-Hosting Costs
All three tools are free. The costs are infrastructure:
| Setup | Monthly Cost |
|---|---|
| Personal laptop (Apple M-series) | $0 |
| Hetzner CAX11 (4GB ARM, for Open WebUI + Ollama) | $4/month |
| Hetzner CPX21 (4GB, for LibreChat stack) | $6.50/month |
| Hetzner CCX13 (GPU-capable, for better performance) | $35+/month |
For a 10-person team using Open WebUI + Ollama with a $20/month VPS, the annual cost is $240. Compare that to $2,400-$4,800/year for ChatGPT Team subscriptions.
Find Your Alternative
Browse all self-hosted AI chat interfaces on OSSAlt — see detailed feature comparisons, deployment guides, and community reviews for Open WebUI, LibreChat, Jan, and every other major self-hosted AI chat platform.