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How to Use Open WebUI in 2026: Complete Guide to Self-Hosted AI Chat Interface

AI Tools January 31, 2026 24 min read

Want a ChatGPT-like interface for your local AI models with zero monthly fees and complete privacy? Open WebUI is the answer. In 2026, it's the most popular self-hosted web interface for running AI models privately, supporting everything from personal use to enterprise team deployments.

This comprehensive guide shows you exactly how to use Open WebUI in 2026, from Docker installation to advanced features like RAG (Retrieval-Augmented Generation), multi-user management, and custom integrations. Whether you're running AI for yourself or your entire organization, you'll learn how to build a private ChatGPT alternative that you fully control.

What is Open WebUI? (And Why It's Essential in 2026)

Open WebUI (formerly known as Ollama WebUI) is an open-source, self-hosted web application that provides a beautiful, ChatGPT-like interface for interacting with local AI models. Think of it as your own private ChatGPT that runs on your infrastructure with your data.

Why Open WebUI Dominates in 2026

  • Self-Hosted Privacy: Your conversations and data never leave your servers
  • Multi-Backend Support: Works with Ollama, LM Studio, OpenAI, and any OpenAI-compatible API
  • ChatGPT-Like UX: Familiar interface that feels like ChatGPT but runs locally
  • Team-Ready: User management, authentication, and role-based permissions built-in
  • Advanced Features: RAG (document chat), web search, function calling, and plugins
  • Zero Ongoing Costs: No per-user fees, no API charges, just your hosting costs
  • Active Development: Rapidly evolving with new features added monthly in 2026

Open WebUI vs. Cloud AI Services

Open WebUI provides: Complete control, unlimited usage, data privacy, custom models, and no vendor lock-in.

Cloud services offer: Zero setup, latest flagship models (GPT-4, Claude), and global availability without infrastructure.

Many organizations use both: Open WebUI for sensitive work and internal tasks, cloud services for cutting-edge capabilities.

What Makes Open WebUI Special in 2026

Feature Open WebUI ChatGPT Web Direct Ollama CLI
Interface Beautiful web UI Beautiful web UI Command line only
Data Privacy 100% self-hosted Sent to OpenAI 100% local
Multi-User Yes, unlimited users Individual accounts Single user
Document Upload (RAG) Built-in Paid tier only Not available
Cost Free (self-host) $20+/month per user Free
Conversation Management Save, organize, share, export Save and organize None
Model Switching Dropdown menu, instant Limited to OpenAI models Command required

How to Install Open WebUI in 2026 (Step-by-Step)

Prerequisites

  • Docker Desktop installed (Windows/Mac) or Docker Engine (Linux)
  • Ollama or LM Studio installed and running (or OpenAI API key)
  • 4 GB+ RAM available for the container
  • Modern web browser (Chrome, Firefox, Safari, Edge)

Method 1: Docker with Ollama (Recommended for 2026)

Single command installation:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:main

This command:

  • Runs Open WebUI in detached mode (-d)
  • Maps port 3000 on your machine to port 8080 in container
  • Connects to Ollama running on your host machine
  • Creates a persistent volume for your data
  • Uses the latest stable version

Access Your Installation

After installation, open your browser and navigate to http://localhost:3000. The first account you create will be the admin account.

Method 2: Docker with GPU Support (CUDA)

For NVIDIA GPU acceleration:

docker run -d -p 3000:8080 --gpus all --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:cuda

Requires NVIDIA Docker runtime installed. GPU support enables:

  • Faster embedding generation for RAG
  • Accelerated image processing
  • Better performance with large documents

Method 3: Docker Compose (Team Deployments)

Create docker-compose.yml:

version: '3.8' services: open-webui: image: ghcr.io/open-webui/open-webui:main container_name: open-webui ports: - "3000:8080" environment: - OLLAMA_BASE_URL=http://host.docker.internal:11434 - WEBUI_SECRET_KEY=your-secret-key-change-this volumes: - open-webui-data:/app/backend/data extra_hosts: - "host.docker.internal:host-gateway" restart: unless-stopped volumes: open-webui-data:

Start with:

docker-compose up -d

Method 4: Native Installation (Advanced)

For users who prefer running without Docker:

Clone and install:

git clone https://github.com/open-webui/open-webui.git cd open-webui npm install npm run build cd backend pip install -r requirements.txt sh start.sh

Native installation offers more control but requires managing Python, Node.js, and dependencies manually.

First-Time Setup

  1. Open browser to http://localhost:3000
  2. You'll see the signup page
  3. Create your admin account (first user = admin automatically)
  4. Log in with your credentials
  5. Open WebUI will detect Ollama models automatically
  6. Start chatting with your local models!

Security Note for Network Deployments

If exposing Open WebUI beyond localhost in 2026, always use HTTPS, strong passwords, and consider implementing additional authentication layers (reverse proxy with auth, VPN, etc.). Never expose to public internet without proper security.

How to Connect Open WebUI to AI Backends

Connecting to Ollama (Default)

Open WebUI auto-detects Ollama running on the default port (11434). If Ollama is running, your models appear automatically.

To verify connection:

  1. Click the model dropdown in chat
  2. Your Ollama models should be listed
  3. If not, check Settings → Connections → Ollama API URL
  4. Ensure it points to http://host.docker.internal:11434 (Docker) or http://localhost:11434 (native)

Connecting to LM Studio

  1. Start LM Studio's local server (usually port 1234)
  2. In Open WebUI, go to Settings → Connections
  3. Enable "OpenAI API"
  4. Set Base URL: http://host.docker.internal:1234/v1
  5. API Key: not required (leave blank or use "dummy")
  6. Models from LM Studio now appear in your model dropdown

Connecting to OpenAI API

Use cloud models alongside local ones:

  1. Settings → Connections → OpenAI API
  2. Enable OpenAI API
  3. Enter your OpenAI API key
  4. GPT-4, GPT-3.5, etc. now appear in model selector
  5. Choose per conversation which backend to use

Multiple Backend Configuration in 2026

Backend Base URL API Key Required Use Case
Ollama (Local) http://host.docker.internal:11434 No Private local models, offline work
LM Studio http://host.docker.internal:1234/v1 No GUI model management, easy switching
OpenAI https://api.openai.com/v1 Yes Access to GPT-4, latest models
Azure OpenAI Custom Azure endpoint Yes Enterprise compliance, data residency
Other Compatible APIs Varies Varies Custom deployments, specialized models

Hybrid Strategy in 2026

Many teams configure multiple backends: Ollama for sensitive data and everyday tasks, OpenAI API for tasks requiring cutting-edge capabilities. Open WebUI makes switching seamless—just select a different model per conversation.

How to Use Open WebUI's Interface

Starting a Conversation

  1. Click "+ New Chat" button in sidebar
  2. Select a model from the dropdown
  3. Type your message and press Enter or click Send
  4. AI responds using the selected model
  5. Continue the conversation—context is maintained automatically

Key Interface Features in 2026

Model Switching Mid-Conversation

  • Click model dropdown anytime during chat
  • Select different model to continue with
  • Previous context is sent to new model
  • Compare responses from different models easily

Conversation Management

  • Rename: Hover over conversation → click menu → rename
  • Archive: Hide old conversations without deleting
  • Delete: Permanently remove conversations
  • Export: Download as JSON, text, or markdown
  • Share: Generate shareable link (configurable in settings)

Message Actions

Action What It Does When to Use
Copy Copy message to clipboard Quickly grab AI responses for use elsewhere
Edit Modify your message and regenerate Refine questions without retyping
Regenerate Get different response to same prompt Explore alternative answers
Continue Ask AI to continue its response When response cuts off mid-thought
Branch Create alternate conversation path Explore different directions without losing original

Advanced Chat Features

  • System Prompts: Set custom behavior per conversation
  • Temperature Control: Adjust creativity vs. consistency
  • Context Length: Control how much history the AI sees
  • Response Length: Set max tokens for answers
  • Stop Sequences: Define when AI should stop generating

Workspace Organization

Open WebUI 2026 includes folders and tags for organizing conversations:

  • Create folders: "Work", "Personal", "Research", etc.
  • Drag conversations into folders
  • Add tags for cross-folder categorization
  • Search across all conversations
  • Filter by model, date, or tags

How to Use RAG (Retrieval-Augmented Generation)

RAG is one of Open WebUI's most powerful features in 2026—it lets you chat with your own documents, creating a private knowledge base the AI can reference.

What is RAG and Why It Matters

RAG (Retrieval-Augmented Generation) enhances AI responses by searching your uploaded documents for relevant context before generating answers. Instead of relying only on training data, the AI pulls information from your files.

Uploading Documents

  1. Click the paperclip icon in chat input
  2. Select "Upload Document"
  3. Choose files (PDF, TXT, DOCX, MD, CSV supported in 2026)
  4. Open WebUI processes and creates embeddings
  5. Document appears in your knowledge base

Using Documents in Conversations

Option 1: Select Documents Per Chat

  1. Start new conversation
  2. Click document icon in chat
  3. Select which documents AI can access
  4. AI now searches these docs when answering

Option 2: Create Document Collections

  1. Go to Settings → Knowledge → Collections
  2. Create collection (e.g., "Company Policies", "Technical Docs")
  3. Add relevant documents to collection
  4. Select collection when starting new chat

RAG Best Practices in 2026

Practice Why It Matters How To Implement
Chunk Size Optimization Better retrieval accuracy Settings → RAG → Chunk Size: 500-1000 characters for most docs
Embedding Model Selection Faster processing or better quality Use all-minilm for speed, bge-large for accuracy
Top-K Results Control context volume Settings → RAG → Top K: 3-5 for focused, 8-10 for comprehensive
Document Naming Easier management and citation Use descriptive names: "Q4_2025_Financial_Report.pdf"
Regular Updates Keep knowledge current Re-upload updated versions, delete outdated docs

Advanced RAG Features

Web Search Integration

In 2026, Open WebUI supports web search alongside document RAG:

  • Enable web search in Settings → Features
  • Configure search engine (DuckDuckGo, Google, Brave, SearXNG)
  • AI can search web for current information
  • Combines web results with your documents

Citation and Source Tracking

  • Enable "Show Citations" in chat settings
  • AI responses include source references
  • Click citation to view original document section
  • Verify information accuracy easily

Multi-Modal RAG

2026 enhancement: Upload images and videos for visual search:

  • Upload diagrams, charts, screenshots
  • AI extracts text and visual information
  • Ask questions about visual content
  • Combine text and image search

Real-World RAG Use Case: Legal Firm

A law firm uploads 500+ case files and legal precedents to Open WebUI. Lawyers ask questions like "What cases set precedent for X?" and get instant answers with citations to specific case documents. All data stays on their private server, ensuring client confidentiality.

How to Manage Users and Permissions

Open WebUI's multi-user features make it perfect for teams in 2026. Unlike ChatGPT where each user needs a subscription, Open WebUI supports unlimited users on your single instance.

User Roles

Role Permissions Best For
Admin Full system access, user management, settings, model configuration IT administrators, system owners
User Chat access, document upload, personal settings, model usage Regular team members
Pending No access until approved New signups awaiting approval

Adding Users

Method 1: Self-Registration (if enabled)

  1. Users visit your Open WebUI URL
  2. Click "Sign Up"
  3. Create account (status: Pending)
  4. Admin approves in Settings → Users
  5. User can now log in

Method 2: Admin-Created Accounts

  1. Admin goes to Settings → Users
  2. Click "Add User"
  3. Enter email, name, password
  4. Set role (User or Admin)
  5. User receives credentials to log in

Privacy and Sharing Controls

Open WebUI 2026 offers granular privacy settings:

Conversation Privacy

  • Private (Default): Only you can see your conversations
  • Shared with Link: Anyone with link can view (read-only)
  • Team Shared: All users in workspace can access
  • Admin Visible: Admins can view for compliance/monitoring

Document Access Controls

  • Documents uploaded by users are private by default
  • Create shared document collections for team access
  • Admin-managed knowledge bases for company-wide info
  • Permission levels: View, Edit, Manage

Team Deployment Configuration

Environment variables for team setup:

ENABLE_SIGNUP=false # Disable self-registration DEFAULT_USER_ROLE=pending # Require admin approval WEBUI_AUTH=true # Require authentication WEBUI_SECRET_KEY=your-strong-secret-key ENABLE_COMMUNITY_SHARING=false # Disable public sharing OAUTH_CLIENT_ID=your-oauth-id # Optional SSO integration

Usage Analytics and Monitoring

Admins in 2026 can track:

  • Active users and login history
  • Model usage statistics (which models are popular)
  • Token consumption per user
  • Storage usage (conversations and documents)
  • System performance metrics

Team Onboarding Tip

Create a shared "Getting Started" conversation with examples, best practices, and common prompts. New users can fork this conversation to hit the ground running with your team's standards.

Advanced Open WebUI Features in 2026

1. Function Calling and Tools

Open WebUI supports function calling for models that have this capability:

  • Define custom tools the AI can invoke
  • Connect to external APIs and services
  • Automate workflows (send emails, create tickets, fetch data)
  • Build AI agents with real-world actions

Example tool definition (weather API):

{ "name": "get_weather", "description": "Get current weather for a location", "parameters": { "type": "object", "properties": { "location": {"type": "string", "description": "City name"} }, "required": ["location"] } }

2. Custom Prompts Library

Create reusable prompts for common tasks:

  • Save frequently used system prompts
  • Share prompt templates across team
  • Version control for prompt engineering
  • Import community prompts

3. Model Presets

Save parameter configurations for different use cases:

Preset Name Temperature Top P Use Case
Precise 0.1 0.5 Factual answers, code, data analysis
Balanced 0.7 0.9 General conversation, explanations
Creative 1.2 0.95 Writing, brainstorming, storytelling
Deterministic 0 0.1 Reproducible outputs, testing

4. API Access

Open WebUI exposes its own API for programmatic access:

Python example:

import requests response = requests.post( 'http://localhost:3000/api/chat', headers={'Authorization': 'Bearer YOUR_TOKEN'}, json={ 'model': 'llama3.3', 'messages': [{'role': 'user', 'content': 'Hello!'}] } ) print(response.json())

5. Plugins and Extensions

2026 brings a plugin ecosystem to Open WebUI:

  • Code execution environments (run Python, JavaScript in chat)
  • Database connectors (query SQL databases)
  • Calendar and scheduling integrations
  • Custom UI themes and layouts
  • Third-party service integrations

6. Voice Input and Output

  • Speech-to-text for message input
  • Text-to-speech for AI responses
  • Multiple voice options and languages
  • Hands-free conversation mode

7. Image Generation Integration

Connect Stable Diffusion or DALL-E for image generation within chat:

  • Configure image generation backend in settings
  • Ask AI to generate images in conversation
  • Supports local (Stable Diffusion WebUI, ComfyUI) and cloud (DALL-E API)
  • Images stored in conversation history

What Can You Do with Open WebUI in 2026?

1. Personal Knowledge Management

  • Upload personal notes, articles, research papers
  • Build second brain with AI assistant
  • Quick search across all saved knowledge
  • Generate summaries and insights from your library

2. Team Collaboration Hub

  • Centralized AI access for entire organization
  • Shared knowledge bases (company docs, policies, procedures)
  • Collaborative conversations with branching
  • Standardized prompts and workflows

3. Customer Support AI

  • Upload product documentation and FAQs
  • Support team uses AI for instant answers
  • Consistent response quality across team
  • Track common questions for improvement

4. Research and Analysis

  • Upload research papers, datasets, reports
  • AI helps analyze trends and patterns
  • Generate literature reviews
  • Cross-reference multiple sources

5. Education and Training

  • Upload course materials and textbooks
  • Students ask questions about curriculum
  • Generate practice problems and quizzes
  • Personalized tutoring at scale

6. Software Development

  • Upload codebase documentation
  • Ask about architecture and patterns
  • Code review assistance
  • Generate boilerplate and tests

Industry-Specific Applications

Industry Open WebUI Application Key Benefit
Healthcare Medical literature search, patient note summarization HIPAA compliance through on-premise deployment
Legal Case law research, contract analysis, document drafting Client-attorney privilege protection
Finance Financial report analysis, compliance checking Regulatory compliance with data sovereignty
Manufacturing Equipment manuals, troubleshooting guides, safety protocols Offline access on factory floor
Government Policy research, document classification, citizen queries Air-gapped deployment for classified networks

Common Open WebUI Issues and Solutions (2026)

Problem: Can't Connect to Ollama

Symptoms: "No models found" or connection errors

Solutions:

  • Verify Ollama is running: ollama list in terminal
  • Check Ollama URL in Settings → Connections
  • Docker users: Ensure --add-host=host.docker.internal:host-gateway was used
  • Test connection: curl http://localhost:11434/api/tags
  • Restart both Ollama and Open WebUI

Problem: RAG Not Finding Relevant Content

Symptoms: AI doesn't reference uploaded documents

Solutions:

  • Verify document upload completed (check status in Knowledge section)
  • Ensure documents are selected for the conversation
  • Adjust RAG settings: increase Top K results
  • Try different chunk size (Settings → RAG)
  • Use more specific queries that match document content
  • Re-upload with different embedding model

Problem: Slow Response Generation

Symptoms: Long wait times for AI responses

Solutions:

  • Use smaller/faster models (7B instead of 70B)
  • Enable GPU acceleration if available
  • Reduce context length in conversation settings
  • Close unnecessary conversations to free memory
  • Check Docker resource limits (increase RAM allocation)
  • Monitor Ollama/LM Studio performance separately

Problem: Users Can't Sign Up

Symptoms: Signup page not working or missing

Solutions:

  • Check if signup is disabled in environment variables
  • Admin must enable: Settings → General → Enable Signup
  • Verify email configuration if email verification is required
  • Clear browser cache and cookies
  • Check Docker logs for errors: docker logs open-webui

Problem: Lost Admin Access

Symptoms: No admin account available

Solutions:

  • First user created is always admin
  • Promote user to admin via database or environment variable
  • Restart with admin creation flag enabled
  • Worst case: Reset database (loses all data)

Problem: Data Not Persisting

Symptoms: Conversations disappear after restart

Solutions:

  • Verify Docker volume is properly mounted: -v open-webui:/app/backend/data
  • Check volume exists: docker volume ls
  • Ensure volume path has write permissions
  • Don't use --rm flag which deletes volumes

Need More Help?

Join the Open WebUI Discord community or GitHub discussions. The 2026 community is highly active with quick responses to troubleshooting questions. Check logs first (docker logs open-webui) before asking for help.

Open WebUI Deployment Options for 2026

1. Single-User Local (Easiest)

Best for: Personal use, learning, testing

  • Run Docker command on your computer
  • Access at localhost:3000
  • No network configuration needed
  • Perfect for privacy-focused individuals

2. Home Network Deployment

Best for: Family/small team sharing

  • Run on always-on computer or NAS
  • Access from any device on home WiFi
  • Use local IP address (e.g., 192.168.1.100:3000)
  • Optional: Set up local domain name with Pi-hole or router

3. VPS/Cloud Deployment

Best for: Remote access, distributed teams

  • Deploy to DigitalOcean, AWS, Azure, or any VPS
  • Set up domain name and SSL certificate
  • Configure firewall and security
  • Access from anywhere with internet

4. On-Premise Enterprise

Best for: Large organizations, compliance requirements

  • Deploy on company infrastructure
  • Integrate with Active Directory/LDAP
  • Set up load balancing and high availability
  • Implement backup and disaster recovery

Deployment Comparison

Option Cost Setup Difficulty Accessibility Performance
Local Desktop $0 Easy Single device Excellent (depends on hardware)
Home Server $0-500 (hardware) Medium Local network Excellent
Cloud VPS $10-100+/month Medium-Hard Global Good (depends on VPS specs)
Enterprise Varies widely Hard Organization-wide Excellent (dedicated resources)

2026 Recommendation

Start local to learn and test. Once comfortable, move to home network for family/small team access. Only deploy to cloud VPS if you need remote access or lack always-on local hardware. Enterprise deployment requires IT expertise—consider consulting if new to this.

Open WebUI Best Practices for 2026

Security Best Practices

  1. Use Strong Passwords: Require complex passwords for all users
  2. Enable HTTPS: Always use SSL/TLS for network deployments
  3. Regular Updates: Keep Open WebUI updated for security patches
  4. Backup Data: Regularly export conversations and documents
  5. Limit Exposure: Don't expose to public internet unless necessary
  6. Monitor Access: Review user activity logs periodically
  7. Network Segmentation: Run on isolated network segment if possible

Performance Optimization

  1. Resource Allocation: Give Docker container adequate RAM (8 GB+ for active use)
  2. Model Selection: Balance quality vs. speed based on use case
  3. Embedding Models: Use smaller embedding models for faster RAG
  4. Context Management: Don't keep unnecessary long conversations in memory
  5. Document Cleanup: Remove outdated documents from knowledge base
  6. GPU Utilization: Enable GPU for embeddings if available

Workflow Efficiency Tips

  • Create template conversations for common tasks
  • Use keyboard shortcuts (Tab for autocomplete, / for commands)
  • Organize with folders and tags from day one
  • Build shared prompt library for team consistency
  • Set up document collections for different projects
  • Export important conversations as backups

Cost Optimization for Teams

Team Size Open WebUI Cost ChatGPT Teams Cost Annual Savings
5 users $0-50/month (hosting) $300/month ($25×12/user) $2,400-3,600/year
25 users $0-200/month (server) $1,500/month $15,600-18,000/year
100 users $0-500/month (infrastructure) $6,000/month $66,000-72,000/year

Note: Savings assume local hardware or cloud VPS costs. Doesn't include model API costs if using cloud backends.

Your Open WebUI 2026 Getting Started Checklist

Prerequisites

  • ☐ Install Docker Desktop or Docker Engine
  • ☐ Install Ollama or LM Studio with at least one model
  • ☐ Verify backend is running (test with ollama list or LM Studio)
  • ☐ Ensure 8 GB+ RAM available

Installation

  • ☐ Run Open WebUI Docker command
  • ☐ Access http://localhost:3000
  • ☐ Create admin account
  • ☐ Verify models appear in dropdown
  • ☐ Send test message to confirm connection

Configuration

  • ☐ Configure backend connections (Ollama/LM Studio/OpenAI)
  • ☐ Set up user accounts (if team deployment)
  • ☐ Configure RAG settings (chunk size, embedding model)
  • ☐ Customize interface (theme, language, defaults)
  • ☐ Set privacy and sharing preferences

First Use

  • ☐ Start conversation with default model
  • ☐ Try switching models mid-conversation
  • ☐ Upload test document and ask questions
  • ☐ Create conversation folder for organization
  • ☐ Export a conversation to test backup

Advanced Setup (Optional)

  • ☐ Set up web search integration
  • ☐ Create custom prompts library
  • ☐ Configure function calling/tools
  • ☐ Set up backup automation
  • ☐ Configure SSL for network access

Final Thoughts: Making Open WebUI Work for You in 2026

Open WebUI represents the democratization of AI technology—powerful capabilities accessible to anyone with a computer, without ongoing subscription costs or data privacy compromises. Whether you're an individual protecting your privacy, a small team seeking cost savings, or an enterprise requiring data sovereignty, Open WebUI delivers.

The key to success with Open WebUI in 2026:

  • Start Simple: Install locally, test with one model, learn the interface
  • Gradually Add Complexity: Introduce RAG, then multi-user, then advanced features
  • Customize for Your Needs: Configure settings, prompts, and workflows that match your use case
  • Engage the Community: Join Discord, share learnings, contribute back

The self-hosted AI movement is thriving in 2026, and Open WebUI is at the forefront. Install it today and take control of your AI infrastructure.

Ready to Deploy Your Private ChatGPT?

Install Open WebUI in 5 minutes with Docker. No credit card, no subscription, no data collection—just powerful self-hosted AI. Visit github.com/open-webui/open-webui to get started.

Frequently Asked Questions

Is Open WebUI really free in 2026?

Yes, Open WebUI is completely open-source and free. You only pay for your infrastructure (computer/server costs) and any cloud AI APIs you choose to use. There are no licensing fees, user limits, or hidden costs.

Can I use Open WebUI commercially?

Yes, Open WebUI is licensed under MIT, allowing commercial use. However, check the licenses of models you use—most open models allow commercial use, but some research models have restrictions.

How many users can Open WebUI support?

There's no hard limit. Small teams (5-25 users) work great on modest hardware. Large deployments (100+ users) require proper infrastructure planning but are absolutely feasible. Scale depends on your hardware/server capacity.

Do I need a GPU to run Open WebUI?

No, but it helps. Open WebUI itself runs fine on CPU. GPUs accelerate model inference (via Ollama/LM Studio) and embedding generation (for RAG). You can start with CPU and add GPU later if needed.

Can Open WebUI work offline?

Yes! When using local backends (Ollama/LM Studio) with downloaded models, Open WebUI works completely offline. This is perfect for air-gapped environments, travel, or privacy-critical work.

How does Open WebUI compare to ChatGPT?

Open WebUI provides similar interface and features but runs on your infrastructure. ChatGPT offers more advanced flagship models but requires internet and sends data to OpenAI. Many use both: Open WebUI for sensitive work, ChatGPT for cutting-edge capabilities.

Can I migrate from ChatGPT to Open WebUI?

Yes. While you can't directly import ChatGPT conversations, you can start fresh with Open WebUI or manually copy important conversations. Many teams run both in parallel during transition.

What's the difference between Open WebUI and Ollama?

Ollama is a backend that runs AI models (like Docker for models). Open WebUI is a web interface for interacting with those models. They work together: Ollama runs the models, Open WebUI provides the user-friendly chat interface.

How do I backup my Open WebUI data?

Export conversations individually or back up the entire Docker volume. For Docker: docker run --rm -v open-webui:/data -v $(pwd):/backup ubuntu tar czf /backup/open-webui-backup.tar.gz /data

Can Open WebUI integrate with existing company systems?

Yes, via API and SSO. Open WebUI supports OAuth/OIDC for authentication (integrate with Google Workspace, Azure AD, etc.) and provides an API for custom integrations with your internal tools.

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