This is week 25 of my “I Used It for a Week” series. Last week I reviewed RunPod, the GPU cloud. This week: the tool that gives you ChatGPT on your own hardware.

Open WebUI is a self-hosted web interface for LLMs. It looks like ChatGPT, works like ChatGPT, but runs on your own servers with your own models.

After a week of using Open WebUI, I think it’s the best way to give your team access to AI without sending data to OpenAI.

How It Works

docker run -d -p 3000:8080 \
  -v open-webui:/app/backend/data \
  --name open-webui \
  ghcr.io/open-webui/open-webui:main

That’s it. Open WebUI runs in Docker and connects to any OpenAI-compatible API: Ollama, LM Studio, vLLM, or cloud providers.

The interface is familiar: chat, file upload, model selection, conversation history. It looks like a polished ChatGPT clone.

Day 1: First Impressions

I connected Open WebUI to my LM Studio server running Qwen 3.6 27B. The interface loaded instantly, and I could start chatting with my local model.

The experience was surprisingly good. The UI is clean, the responses are fast, and the model selection works seamlessly.

I shared the URL with my team. Now everyone can access the local model through a browser. No API keys, no subscriptions, no data leaving our network.

Day 2-3: Features

Open WebUI has features that ChatGPT doesn’t:

• Multi-model support: Switch between models mid-conversation
• RAG (Retrieval-Augmented Generation): Upload documents and chat with them
• Custom system prompts: Save and reuse prompt templates
• User management: Add team members with different permissions
• Conversation history: Search and organize past chats

The RAG feature is particularly useful. I uploaded our codebase documentation and could ask questions about it. The answers were grounded in our actual docs, not generic knowledge.

Day 4-5: Team Use

Open WebUI’s killer use case: giving your team access to AI without cloud dependencies.

I set it up for my team of 5:

• Each person gets their own account
• Conversations are private to each user
• Admin can see usage statistics
• No one sends data to external APIs

The onboarding was simple: share the URL, create accounts, and everyone is productive in minutes.

What Blew Me Away

Self-hosted privacy

Your data stays on your servers. No cloud APIs, no data transmission, no compliance concerns. For companies with strict data policies, this is essential.

Multi-model support

Switch between models mid-conversation. Use a fast model for quick questions and a powerful model for complex tasks. All through one interface.

Team features

User management, conversation history, and usage statistics make it practical for teams.

Open source

MIT license. You can modify it, extend it, or integrate it with your existing tools.

What Frustrated Me

Setup complexity

Docker is easy if you know it, but intimidating if you don’t. Non-technical users need help getting started.

No mobile app

Open WebUI is web-based only. No native mobile app. The mobile web experience is functional but not as polished as ChatGPT’s app.

Model quality depends on your hardware

If you’re running local models, the quality depends on your hardware. A 27B model on 32GB RAM is good but not ChatGPT-level.

No GPT-4 class models locally

Open WebUI works best with local models, but local models can’t match GPT-5.6 or Claude Sonnet 5 quality. You can connect to cloud APIs, but then you lose the privacy benefit.

Customization limitations

Open WebUI is configurable but not infinitely customizable. If you need a highly tailored UI or workflow, you may need to modify the source code.

Real-World Use Cases

Startup with 5 developers. We set up Open WebUI with LM Studio running Qwen 3.6 27B. Each developer gets access to a coding assistant without API costs. Total setup time: 30 minutes.

Enterprise team with compliance requirements. A team at a healthcare company needed AI assistance but couldn’t send patient data to external APIs. Open WebUI with local models solved the compliance problem.

Education institution. A university gave students access to AI through Open WebUI. Students can experiment with AI without needing individual API keys or credit cards.

Personal use. I use Open WebUI at home for personal projects. The interface is cleaner than running LM Studio directly, and I can access it from any device on my network.

Open WebUI vs ChatGPT vs Claude

• ChatGPT: Best model quality, best mobile app, easiest to use. But sends data to OpenAI.
• Claude: Best reasoning, best for complex tasks. But sends data to Anthropic.
• Open WebUI: Best privacy, best for teams, self-hosted. But depends on your local model quality.

They’re complementary. Use ChatGPT for personal use, Claude for complex tasks, and Open WebUI for team access with privacy requirements.

Would I Keep Using?

Yes. Open WebUI is now part of my team’s workflow. The privacy benefits and team features justify the setup effort.

Rating: 8/10 — Best self-hosted ChatGPT alternative. The setup complexity and mobile experience are minor issues.

FAQ

What is Open WebUI?

Open WebUI is a self-hosted web interface for LLMs. It provides a ChatGPT-like experience using your own models and servers.

How do I install Open WebUI?

Run the Docker command from the documentation. It requires Docker and about 5 minutes of setup.

Can I use Open WebUI with cloud APIs?

Yes. Open WebUI connects to any OpenAI-compatible API: Ollama, LM Studio, OpenAI, Anthropic, etc.

Is Open WebUI secure?

The application itself is secure. Your data stays on your servers. You control access through user management and permissions.

Related: Open WebUI Complete Guide · Self-Hosted AI Setup · Best Self-Hosted AI Tools 2026

Next week: I Used MCP Hub for a Week — the central place to discover MCP servers.