# Open WebUI Docs Full Corpus Every docs page concatenated into a single Markdown file. When citing sources, cite canonical HTML URLs. Generated: 2026-08-13T04:44:23.910Z --- # Open WebUI Source: https://docs.openwebui.com/ Open WebUI is **a home for AI**, a self-hosted AI platform that's **[extensible](https://docs.openwebui.com/features/extensibility/plugin/)**, **[feature-rich](https://docs.openwebui.com/features/)**, user-friendly, and built to run **[entirely offline](https://openwebui.com/sovereign-ai)**. With support for **Ollama** and **OpenAI-compatible APIs**, it gives you a powerful, provider-agnostic interface for both local and cloud-based models. ![Open WebUI: a self-hosted AI platform connecting local and cloud models with tools and knowledge](/images/banners/home-light.svg)![Open WebUI: a self-hosted AI platform connecting local and cloud models with tools and knowledge](/images/banners/home-dark.svg) ![GitHub stars](https://img.shields.io/github/stars/open-webui/open-webui?style=social) ![GitHub forks](https://img.shields.io/github/forks/open-webui/open-webui?style=social) [![Discord](https://img.shields.io/badge/Discord-Open_WebUI-blue?logo=discord&logoColor=white)](https://discord.gg/5rJgQTnV4s) --- ## Quick Start ``` docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main ``` Then open [http://localhost:3000](http://localhost:3000). ![Open WebUI running a live analysis: Claude Opus 5 reads a spreadsheet through Open Terminal and renders an interactive revenue dashboard inline in the chat](/images/landing/hero.png) Powered by [Open Terminal](/features/open-terminal) and some of our [amazing community built plugins](/features/extensibility/community). For GPU support, Docker Compose, and more → [Full Docker guide](/getting-started/quick-start) ``` pip install open-webui open-webui serve ``` Then open [http://localhost:8080](http://localhost:8080). ``` curl -LsSf https://astral.sh/uv/install.sh | sh DATA_DIR=~/.open-webui uvx --python 3.11 open-webui@latest serve ``` Then open [http://localhost:8080](http://localhost:8080). Download the desktop app from [**github.com/open-webui/desktop**](https://github.com/open-webui/desktop). It runs Open WebUI natively on your system without Docker or manual setup. > **info** > > For production deployments, install via **Docker** or **Python**. > **Running? Read this next.** > > Installed Open WebUI but not sure where to start? The [**Essentials for Open WebUI**](/getting-started/essentials) guide covers the six things every new user needs to know: plugins, tool calling, task models, context management, RAG, and Open Terminal. --- ## Getting Started - [**Quick Start**](/getting-started/quick-start): Docker, Python, Kubernetes install options - [**Connect a Provider**](/getting-started/quick-start/connect-a-provider): Ollama, OpenAI, Anthropic, vLLM, and more - [**Essentials for Open WebUI**](/getting-started/essentials): Start here after your first install. Plugins, tool calling, task models, context management, RAG, Open Terminal. - [**Connect an Agent**](/getting-started/quick-start/connect-an-agent): Open WebUI Computer, Hermes Agent, OpenClaw, and other autonomous AI agents - [**Updating**](/getting-started/updating): Keep your instance current - [**Development Branch**](/getting-started/quick-start): Help test the latest changes before stable release - [**Advanced Topics**](/getting-started/advanced-topics): Scaling, logging, and advanced configuration --- ## Explore - [**Features**](/features): Discover what Open WebUI can do - [**Tutorials**](/tutorials): Step-by-step guides - [**FAQ**](/faq): Common questions answered - [**Troubleshooting**](/troubleshooting): Fix common issues - [**Reference**](/reference): Environment variables and API details --- ## Open WebUI Computer [**Open WebUI Computer**](/ecosystem/computer) is the cutting-edge agent harness and runtime for your real machine. You install one app, add AI (an API key, a local model, or a coding-agent subscription you already have like Claude Code or Codex), and it works on the actual files, branches, services, and tools already on that computer, with approvals and plan mode. The file the agent edits is the file on your disk; the terminal it uses is the terminal on your machine. Run Computer with uv: ``` uvx cptr@latest run ``` Then create an account and open a folder. Because it's your whole machine, you get the rest for free: files, editor, terminal, git, previews, and agent chats in any browser, from your desk or your phone; an assistant you can message from Telegram or WhatsApp; scheduled agents that report back to you. Everything runs locally on hardware you own, nothing hosted elsewhere. Computer and Open WebUI are one ecosystem moving at two speeds, on purpose. **Open WebUI** is the stable platform: enterprise-ready, multi-user, what teams and organizations deploy and rely on. **Computer** moves faster: new real-machine agent capabilities are built and shipped there first, hardened in daily use, and graduated into Open WebUI where they fit. If you want the bleeding edge of what we're building, it lands in Computer first. - New to it? [What is Computer?](/ecosystem/computer/what-is-computer) · [Quickstart](/ecosystem/computer/quickstart) · [Use cases](/ecosystem/computer/use-cases/) - Already run Open WebUI? [Use a Computer workspace as a model in Open WebUI](/ecosystem/computer/automate/open-webui) --- ## Also by Open WebUI - [**open-terminal**](https://github.com/open-webui/open-terminal): Turn Open WebUI into a full agent harness with a real action runtime: sandboxed files, shell, code execution, previews, and artifacts. - [**oikb**](https://github.com/open-webui/oikb): Keep your Open WebUI knowledge bases in sync. Watches local folders, GitHub repos, S3 buckets, Confluence, and 40+ other sources. - [**mcpo**](https://github.com/open-webui/mcpo): MCP-to-OpenAPI proxy. Use any MCP tool server with Open WebUI (or any OpenAPI client) without custom glue code. --- ## Enterprise Need **custom branding**, **SLA support**, or **Long-Term Support (LTS)**? → [Learn about Enterprise plans](/enterprise) --- ## Get Involved - [**Contributing**](/contributing): Help build Open WebUI - [**Development Setup**](/getting-started/advanced-topics/development): Run the project locally from source - [**Discord**](https://discord.gg/5rJgQTnV4s): Join the community - [**GitHub**](https://github.com/open-webui/open-webui): Report issues, submit PRs - [**Careers**](https://careers.openwebui.com/): Join our team --- ## Sponsors Emerald --- Jade --- [Open WebUI](https://openwebui.com) [![Open WebUI](/images/favicon.png) On a mission to build the best AI user interface.](https://openwebui.com) --- ## Acknowledgements [![A16z](/assets/images/a16z-58aeed7bc9f9a7894b5f3e59192d88d3.png) A16z Open Source AI Grant 2025](https://a16z.com/advancing-open-source-ai-through-benchmarks-and-bold-experimentation/)[![Mozilla](/assets/images/mozilla-c6f20205901846103930d13dd5f57ada.png) Mozilla Builders 2024](https://builders.mozilla.org/)[![GitHub](/assets/images/github-9561a29eaa5e059e087a198bedf703ce.png) GitHub Accelerator 2024](https://github.com/accelerator) --- ## For LLMs and coding agents Machine-readable entry points to this documentation: - [llms.txt](https://docs.openwebui.com/llms.txt): curated index of every docs page with short descriptions. - [llms-full.txt](https://docs.openwebui.com/llms-full.txt): every docs page concatenated into a single Markdown file. - [agents.txt](https://docs.openwebui.com/agents.txt): concise instructions for agents using these docs. - [api/search?q=YOUR_QUERY](https://docs.openwebui.com/api/search?q=YOUR_QUERY): deterministic docs search. All files are generated fresh on every deploy. --- # Alternatives to Open WebUI ![Alternatives to Open WebUI: local models, desktop apps, RAG tools, and cloud AI options compared against Open WebUI](/images/banners/alternatives-light.svg)![Alternatives to Open WebUI: local models, desktop apps, RAG tools, and cloud AI options compared against Open WebUI](/images/banners/alternatives-dark.svg) Source: https://docs.openwebui.com/alternatives The AI space is full of great projects, and we're genuinely happy about that. More tools means more people get access to AI in a way that works for them. We get asked "what else is out there?" a lot, so we put this list together. If Open WebUI isn't quite the right fit for your use case, these are tools we'd point you to without hesitation. We've actually used them, built alongside them, or just think they do something really well. Everything listed here is free to get started with. ## How to Choose - **Running local models?** Start with [Ollama](/alternatives/ollama) or [llama.cpp](/alternatives/llama-cpp), both pair natively with Open WebUI - **Want a desktop app?** [LM Studio](/alternatives/lm-studio) or [Jan](/alternatives/jan) are excellent standalone options - **Need document Q&A?** [AnythingLLM](/alternatives/anythingllm) makes private RAG simple - **Multi-provider chat?** [LibreChat](/alternatives/librechat) handles this well - **Building AI workflows?** [Dify](/alternatives/dify) has a visual workflow designer - **Want AI that just works?** [ChatGPT](/alternatives/chatgpt), [Claude](/alternatives/claude), and [Gemini](/alternatives/gemini) are some of the best AI products in the world: frontier models, polished interfaces, fast iteration, and very little setup. Their models are also available through Open WebUI via API. --- ## All Alternatives | Tool | What It's Great For | License | Works with Open WebUI | | | --- | --- | --- | --- | --- | | Ollama | The local model runner that made self-hosted AI feel approachable | Open Source (MIT) | Native integration | Learn more → | | llama.cpp | Foundational local inference work that opened the door for so much of the ecosystem | Open Source (MIT) | Via API | Learn more → | | LM Studio | A polished desktop experience for discovering, downloading, and running local models | Proprietary (free) | Via API | Learn more → | | Jan | A thoughtful, privacy-first desktop app for local AI | Open Source (Apache 2.0) | Via API | Learn more → | | AnythingLLM | A focused, practical document Q&A workspace | Open Source (MIT) | | Learn more → | | LibreChat | A capable self-hosted multi-provider chat interface with a strong community | Open Source (MIT) | | Learn more → | | Msty | A refined desktop hub for working across local and cloud models | Proprietary (free tier) | | Learn more → | | Onyx | Serious enterprise search and knowledge access with a deep connector catalog | Source Available (MIT core + Enterprise License for ee/) | | Learn more → | | Dify | A strong visual workflow builder for teams shipping LLM applications | Source Available (modified Apache 2.0) | Via API | Learn more → | | ChatGPT / OpenAI | The product and team that brought modern AI into everyday life | Commercial (free tier) | Via OpenAI API | Learn more → | | Claude / Anthropic | Exceptional writing, long-context reasoning, and developer tooling | Commercial (free tier) | Via Anthropic API | Learn more → | | Gemini / Google | Strong multimodal AI with deep Google ecosystem integration | Commercial (free tier) | Via Google AI API | Learn more → | Open WebUI itself contains code under [multiple licenses](/license). The latest components are under the Open WebUI License, which includes a branding preservation requirement, while prior contributions retain their respective original license terms. Every project on this list is built by people who care about making AI more accessible. That pushes all of us, Open WebUI included, to be better. We'd love to be your first choice, but we'd rather you have great options than no options. --- ## Frequently Asked Questions **Is Open WebUI free?** Yes. The community edition is free for unlimited users. Enterprise plans are also available. **Can I self-host Open WebUI?** Yes. Open WebUI runs on your own infrastructure via Docker, Kubernetes, pip, or the desktop app. Your data stays on your hardware. **What models does Open WebUI support?** Open WebUI connects to any OpenAI-compatible API, plus native Ollama integration. This includes OpenAI, Anthropic, Google, Azure, AWS Bedrock, llama.cpp, LM Studio, and hundreds of other providers. _Last updated: August 2026_ --- # Open WebUI & AnythingLLM Source: https://docs.openwebui.com/alternatives/anythingllm _Last updated: August 2026_ [AnythingLLM](https://anythingllm.com/) by Mintplex Labs is one of our favorite projects in the local AI space. They've made private document Q&A genuinely accessible, the workspace-based approach to organizing knowledge is intuitive, and the team behind it is great. If you're looking for a straightforward way to chat with your documents locally, AnythingLLM is well worth a look. [GitHub](https://github.com/Mintplex-Labs/anything-llm) · [MIT License](https://github.com/Mintplex-Labs/anything-llm/blob/master/LICENSE) --- ## What AnythingLLM Does Well - **Document Q&A made simple** so you can upload PDFs, code repos, and websites and start asking questions immediately - **Workspace model** providing clean separation of different knowledge bases and conversations - **Embedding customization** with control over chunking, overlap, and embedding model selection - **Desktop app** for a standalone local experience without Docker or servers - **Cloud deployment option** for teams that want hosted document Q&A - **Privacy-first** with everything running locally so your documents stay on your machine - **Multi-modal support** for handling images and other file types alongside text - **Agent support** with built-in capabilities for tool use and web search - **Active development** with a responsive team and frequent releases - **MIT licensed** --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) for delegated and scheduled work - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Advanced RAG pipeline** with 13 vector databases, 8 extraction engines, hybrid BM25 + vector search with cross-encoder reranking, and agentic retrieval - **Platform breadth** including Chat, Notes, Channels, Automations, Open Terminal, voice/video calls, and image generation - **Team features** including Channels for real-time collaboration, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Model agents** that wrap any model with instructions, tools, knowledge, and parameters - **Enterprise scale** with Kubernetes, horizontal scaling, Redis-backed sessions, OpenTelemetry, and analytics --- ## At a Glance | | Open WebUI | AnythingLLM | | --- | --- | --- | | Focus | Full AI platform with knowledge, tools, and team features | Document Q&A and workspace-based RAG | | RAG approach | 13 vector DBs, 8 extraction engines, hybrid search, reranking | Built-in vector DB with straightforward document ingestion | | Organization | Folders, tags, knowledge bases, notes, channels | Workspaces with dedicated knowledge | | Multi-provider | Ollama, OpenAI, Anthropic, Google, Azure, Bedrock, and more | Ollama, OpenAI, Anthropic, and more | | Extensibility | Python tools, MCP, OpenAPI, pipelines | Agent tools and web search | | Desktop app | Yes | Yes | | Multi-user | SSO/OIDC, LDAP, SCIM 2.0, RBAC, groups | Multi-user with permissions | | License | Open WebUI License | MIT | --- ## When to Use Each **Choose AnythingLLM if** you mostly want to chat with your documents. The workspace model keeps different projects cleanly separated, and the desktop app makes it easy to get started without any server setup. **Choose Open WebUI if** you need a broader platform with team collaboration, multi-provider support, extensibility, or enterprise features alongside document Q&A. **They solve different problems.** AnythingLLM focuses on making document Q&A as simple as possible. Open WebUI takes a wider view with chat, knowledge, collaboration, and tools. Both are good at what they do. --- _Two projects making private AI and document Q&A accessible. Different scope, same commitment to keeping your data under your control._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **How do AnythingLLM and Open WebUI compare?** AnythingLLM leans into document Q&A with its workspace model. Open WebUI also has knowledge bases, team features, extensibility, and multi-provider support. They have different strengths. **Is AnythingLLM free?** Yes. AnythingLLM is MIT licensed. There's a free desktop app and a self-hosted Docker version. --- **Related:** [Open WebUI & LibreChat](/alternatives/librechat) · [Open WebUI & Dify](/alternatives/dify) · [Open WebUI & Ollama](/alternatives/ollama) --- # Open WebUI & ChatGPT Source: https://docs.openwebui.com/alternatives/chatgpt _Last updated: August 2026_ [ChatGPT](https://chat.openai.com/) by OpenAI brought modern AI into everyday life for hundreds of millions of people and set the bar for what a conversational AI experience should feel like. It changed how the world thinks about AI, and it continues to inspire us. We use it daily and learn from the work behind it: the research, engineering, design, safety work, infrastructure, product judgment, and support that make a product at this scale feel natural. The GPT-5.6 family, ChatGPT agent, ChatGPT Images, and the constant pace of product innovation have kept ChatGPT at the forefront, and honestly, it keeps pushing us to make Open WebUI better too. Open WebUI is built in a category ChatGPT helped create. The people at OpenAI made AI feel useful, approachable, and worth bringing into everyday work, not just labs and demos. Their work raised the bar for everyone building in this space. Open WebUI is for people and teams who want to run the interface themselves, connect the models they choose, and adapt the stack to their environment. Commercial · Free tier available --- ## What ChatGPT Does Well - **Frontier models** including the GPT-5.6 family - **Writing and code blocks** for long-form drafting, editing, and code work inside conversations - **Projects** for organizing conversations with persistent context and custom instructions - **Deep research** that synthesizes information across multiple sources into comprehensive reports - **Refined experience** from years of iteration on the interface - **GPT Store** with an ecosystem of custom GPTs built by the community - **Multimodal** with vision, voice, ChatGPT Images, and code execution - **Memory** that remembers context across conversations - **ChatGPT agent** for agentic web browsing and task automation - **Enterprise tier** with SSO, admin controls, and data privacy commitments - **Zero setup** where you sign up and start, no installation needed --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations), on the model of your choice rather than one vendor's - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Self-hosted** so the platform itself runs on your hardware - **Any model, any provider** so you can use OpenAI models available to your API account _and_ Claude _and_ Gemini _and_ local models all in one interface - **Knowledge & RAG** for building knowledge bases from your documents with advanced retrieval - **Team platform** with Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full sandboxed computing environment - **Free community edition** for unlimited users on your own infrastructure --- ## At a Glance | | Open WebUI | ChatGPT | | --- | --- | --- | | Models | Any model from any provider | OpenAI models available in ChatGPT, depending on plan | | Data | Self-hosted, your infrastructure | Cloud-hosted by OpenAI | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Projects with files, memory, and project context | | Custom agents | Model agents with tools, knowledge, and parameters | Custom GPTs via GPT Store | | Code execution | Python in-browser + Open Terminal | Built-in code interpreter | | Extensibility | Python tools, MCP, OpenAPI, pipelines | GPT Actions and Plugin Directory | | Pricing | Free community edition; Enterprise plans available | Free, Go, Plus, Pro, Business, and Enterprise plans | --- ## When to Use Each **Choose ChatGPT if** you want the most polished direct path to OpenAI's best work. No installation, no configuration, just sign up and start. The native experience with Projects, memory, voice, ChatGPT agent, image generation, and deep research features is excellent and constantly improving. **Choose Open WebUI if** you want to run on your own infrastructure, connect to multiple providers in one interface, build knowledge bases from your documents, or need team features like RBAC and SSO included in the free community edition. **Use both.** Many people do. Connect Open WebUI to the OpenAI API and use OpenAI models alongside Claude, Gemini, and local models, all in one place. Use ChatGPT directly when you want the full OpenAI product experience, and Open WebUI when you need your own knowledge bases, tools, permissions, or team workspace. --- ## Use OpenAI Models Through Open WebUI Open WebUI connects to the OpenAI API, so OpenAI models available to your API account are available alongside Open WebUI's knowledge management, tools, and team features. **How to connect:** 1. Get an API key from [platform.openai.com](https://platform.openai.com/) 2. In Open WebUI, go to **Admin → Settings → Connections** 3. Add a new OpenAI connection with your API key 4. OpenAI models available to your API account will appear in your model selector Many users run OpenAI models for complex reasoning alongside local models via Ollama for privacy-sensitive tasks, all in the same interface. --- _ChatGPT made AI useful and approachable at global scale. Open WebUI helps teams bring OpenAI models, and others, into infrastructure they control._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I self-host ChatGPT?** Not ChatGPT itself, but Open WebUI connects to the OpenAI API so you can use OpenAI models available to your API account. Open WebUI runs on your infrastructure, though API calls still go to OpenAI. **Can I use OpenAI models in Open WebUI?** Yes. Add your OpenAI API key in Settings and OpenAI models available to your API account appear in the model selector. **Is Open WebUI a ChatGPT alternative?** Open WebUI can connect to the OpenAI API, so you can use OpenAI models available to your API account. Open WebUI runs on your own infrastructure, though API calls still go to the provider. It also supports connecting to other providers. **Can I use ChatGPT and local models together?** Yes. Many users run OpenAI for complex reasoning alongside local models via Ollama for privacy-sensitive tasks, all in the same Open WebUI interface. --- **Related:** [Open WebUI & Claude](/alternatives/claude) · [Open WebUI & Gemini](/alternatives/gemini) · [Open WebUI & Ollama](/alternatives/ollama) --- # Open WebUI & Claude Source: https://docs.openwebui.com/alternatives/claude _Last updated: August 2026_ [Claude](https://claude.ai/) by Anthropic has earned a loyal following for writing that feels considered, reasoning that holds up over long context, and a product experience that gives work somewhere to land. We count ourselves among those fans, and we use Claude daily. The model research, long-context engineering, safety work, product restraint, and developer tooling all come through in the product. Artifacts made outputs easier to inspect and refine, Claude Code brought Claude into real development workflows, and MCP gave the ecosystem a shared language for connecting models to tools and data. The people at Anthropic have pushed the whole ecosystem forward. Claude made careful analysis, editable outputs, agentic coding, and tool/data connections feel like natural parts of working with AI, and it shows how good a focused model-and-product experience can be. Open WebUI fits around that when teams want to use Claude alongside their own models, knowledge, tools, and workflows. Commercial · Free tier available --- ## What Claude Does Well - **Writing and reasoning** with thoughtful, nuanced responses and careful analysis - **Extended thinking** that shows step-by-step reasoning for complex problems in real time - **Large context windows** up to 200k tokens for working with large documents and codebases - **Artifacts** for interactive outputs (code, documents, visualizations) alongside the conversation - **Claude Code** for agentic coding directly in your terminal - **Computer use** that lets Claude interact with desktop applications and web interfaces - **MCP (Model Context Protocol)** which Anthropic created to standardize how AI tools connect to data sources - **Safety-first design** through Anthropic's constitutional AI approach - **Strong at code** with excellent code generation, review, and debugging - **Projects** for organizing conversations with persistent context and instructions --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations), driving Claude and every other model the same way - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Any model, one interface** so you can use Claude _alongside_ GPT-5.6, Gemini, and local models - **Self-hosted** so the platform itself runs on your infrastructure - **Knowledge & RAG** for persistent knowledge bases with advanced retrieval - **Team platform** with Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full sandboxed computing environment - **Free community edition** for unlimited users on your own infrastructure --- ## At a Glance | | Open WebUI | Claude | | --- | --- | --- | | Models | Any model from any provider | Anthropic's Claude model family | | Extended thinking | Supported for models that offer it (including Claude via API) | Native extended thinking | | Context window | Depends on the model you connect | Up to 200k tokens | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Projects with persistent context | | Code execution | Python in-browser + Open Terminal | Artifacts with interactive code | | Data | Self-hosted, your infrastructure | Cloud-hosted by Anthropic | | Pricing | Free community edition; Enterprise plans available | Free tier, Pro, Team, and Enterprise plans | --- ## When to Use Each **Choose Claude if** you want the best writing and reasoning experience available, especially for long-context work, code review, or nuanced analysis. The extended thinking mode is particularly strong for complex problems. Claude Code and computer use push the boundaries of what AI can do autonomously. **Choose Open WebUI if** you want to use Claude alongside other models in one interface, build persistent knowledge bases, or need team collaboration features. Open WebUI also supports Claude's extended thinking via the API. **Use both.** Connect Open WebUI to the Anthropic API and use Claude for deep analysis alongside GPT-5.6 for other tasks and local models for privacy-sensitive work. Use claude.ai directly when you want Artifacts, Projects, or computer use. --- ## Use Claude Through Open WebUI Claude models are available through Open WebUI via the Anthropic API. Many Open WebUI users run Claude as their primary model, getting Claude's reasoning alongside Open WebUI's knowledge bases, tools, and team features. **How to connect:** 1. Get an API key from [console.anthropic.com](https://console.anthropic.com/) 2. In Open WebUI, go to **Admin → Settings → Connections** 3. Add a new connection with your Anthropic API key and the base URL `https://api.anthropic.com/v1` 4. Claude models will appear in your model selector You can use Claude for complex analysis and writing while routing simpler tasks to local models via Ollama, all in the same interface. --- _Claude raised the bar for thoughtful writing, long-context work, agentic coding, and tool standards. Open WebUI lets teams use Claude where they already manage their models, knowledge, tools, and workflows._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I self-host Claude?** Not Claude itself, but you can use Claude models through Open WebUI via the Anthropic API. Open WebUI itself runs on your infrastructure, though API calls still go to Anthropic. **Can I use Claude in Open WebUI?** Yes. Add your Anthropic API key in Settings and Claude models appear in the model selector. **Can I use Claude and ChatGPT together?** Yes, Open WebUI supports connecting to multiple providers at once. **Does Open WebUI support Claude's extended thinking?** Yes. Extended thinking is supported for models that offer it, including Claude via the Anthropic API. --- **Related:** [Open WebUI & ChatGPT](/alternatives/chatgpt) · [Open WebUI & Gemini](/alternatives/gemini) · [Open WebUI & Ollama](/alternatives/ollama) --- # Open WebUI & Dify Source: https://docs.openwebui.com/alternatives/dify _Last updated: August 2026_ [Dify](https://dify.ai/) by LangGenius takes a fundamentally different approach to AI tooling. Where many tools on this page focus on conversation, Dify focuses on _building_: visual workflow design, agent orchestration, prompt engineering, and deploying AI-powered applications. If you think of AI as a platform for building products, automations, and user-facing features, Dify is worth a serious look. [GitHub](https://github.com/langgenius/dify) · [Source Available (modified Apache 2.0)](https://github.com/langgenius/dify/blob/main/LICENSE) --- ## What Dify Does Well - **Visual workflow builder** with drag-and-drop interface for designing complex AI pipelines and logic - **Agent framework** for building autonomous agents that reason, use tools, and take actions - **Prompt engineering IDE** for crafting, versioning, testing, and comparing prompts in a dedicated environment - **Workflow marketplace** for sharing and importing community-built workflows and templates - **Model routing** with smart routing across multiple providers for cost and capability optimization - **RAG pipeline** with document ingestion, processing, and retrieval built in - **Batch processing** for running prompts and workflows against large datasets - **Annotation and feedback** for collecting human feedback to improve AI outputs over time - **Observability** including integrated monitoring, logging, and cost tracking for production use - **Backend-as-a-Service** for deploying AI apps as APIs instantly - **Embeddable widget** for adding AI chat to any website or application - **Strong community** with a large and active contributor and user base --- ## What Open WebUI Does Well - **Full agentic platform** where the model works through [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode), [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) inside a conversation-first workspace - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Any model, any provider** including Ollama, OpenAI, Anthropic, Google, Azure, and Bedrock in one interface - **Knowledge & RAG** with 13 vector databases, 8 extraction engines, and hybrid search with reranking - **Team collaboration** including Channels, model agents, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full sandboxed computing environment for code execution - **Simpler deployment** with a single Docker container to get started --- ## At a Glance | | Open WebUI | Dify | | --- | --- | --- | | Primary focus | AI chat platform with knowledge, tools, and team features | AI application builder with visual workflows | | Approach | Conversation-first | Build-first | | Workflow building | Python tools and pipelines | Visual drag-and-drop workflow designer | | RAG | 13 vector DBs, 8 extraction engines, hybrid search | Built-in RAG pipeline | | Agent capabilities | Model agents with bound tools and knowledge | Agent framework with reasoning and tool use | | Multi-provider | Any OpenAI-compatible API + Ollama | Multi-provider with model routing | | Observability | OpenTelemetry, analytics dashboards | Built-in monitoring, logging, and cost tracking | | License | Open WebUI License | Source Available (modified Apache 2.0 with commercial restrictions) | --- ## When to Use Each **Choose Dify if** you want to build AI-powered applications with visual workflows. The drag-and-drop builder, prompt IDE, and agent framework are designed for developers and product teams who are creating AI features, not just chatting. **Choose Open WebUI if** your team needs a daily AI workspace for chat, knowledge management, and collaboration. Open WebUI focuses on using AI rather than building AI applications. **Use both.** Dify exposes an OpenAI-compatible API. Connect Open WebUI to Dify's API and your Dify workflows appear as models in Open WebUI. Build in Dify, use in Open WebUI. --- ## Use Them Together Dify exposes an OpenAI-compatible API for any workflow or app you build. You can connect Open WebUI to Dify's API endpoint to use your Dify-built AI applications as models inside Open WebUI, combining Dify's workflow orchestration with Open WebUI's chat interface, knowledge management, and team features. **How to connect:** 1. In Dify, publish your app and copy the API endpoint and key 2. In Open WebUI, go to **Admin → Settings → Connections** 3. Add a new OpenAI-compatible connection with Dify's API URL and key 4. Your Dify apps will appear as models in Open WebUI --- _Dify is for building AI applications. Open WebUI is for using AI daily. The AI ecosystem needs both builders and users._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **How do Dify and Open WebUI compare?** Dify takes a visual, workflow-first approach to building AI applications. Open WebUI leans more toward conversation and daily AI use. They come at AI from different angles, and many teams could use both. **Can I use Dify with Open WebUI?** Yes. Dify exposes an OpenAI-compatible API. Connect Open WebUI to Dify's API to use your Dify workflows as models inside Open WebUI. **Is Dify free?** The community edition is free to self-host. Dify is source available under a modified Apache 2.0 license. --- **Related:** [Open WebUI & Onyx](/alternatives/onyx) · [Open WebUI & LibreChat](/alternatives/librechat) · [Open WebUI & AnythingLLM](/alternatives/anythingllm) --- # Open WebUI & Gemini Source: https://docs.openwebui.com/alternatives/gemini _Last updated: August 2026_ [Gemini](https://gemini.google.com/) brings Google's AI research into a consumer product with strong multimodal capabilities (text, vision, audio, code), generous context windows, and natural integration with Google Workspace. Gemini 3.5 Pro is among the strongest models available for code and complex tasks. Commercial · Free tier available --- ## What Gemini Does Well - **Multimodal strength** across text, images, audio, video, and code in a single model - **Google Workspace integration** that works naturally with Gmail, Docs, Drive, and other Google tools - **Gems** for creating custom AI personas with specific instructions and behavior - **NotebookLM** for turning documents into interactive study guides and audio overviews - **Deep Research** that conducts multi-step research and produces comprehensive reports - **Generous context windows** with Gemini 3.5 Pro handling large documents and codebases - **Competitive API pricing** as one of the most cost-effective APIs for high-quality models - **Code generation** where Gemini 3.5 Pro is among the strongest for code tasks - **Google Search grounding** with responses backed by Google's search infrastructure - **Zero setup** and available immediately through your Google account --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations), driving Gemini and every other model the same way - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Any model, one interface** so you can use Gemini _alongside_ Claude, GPT-5.6, and local models - **Self-hosted** so the platform itself runs on your infrastructure - **Knowledge & RAG** for persistent knowledge bases with advanced retrieval - **Team platform** with Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full sandboxed computing environment --- ## At a Glance | | Open WebUI | Gemini | | --- | --- | --- | | Models | Any model from any provider | Gemini model family | | Multimodal | Depends on connected models | Native text, vision, audio, video, code | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Google Search grounding, file uploads | | Ecosystem | Connects to any API via MCP/OpenAPI | Deep Google Workspace integration | | Data | Self-hosted, your infrastructure | Cloud-hosted by Google | | Pricing | Free community edition; Enterprise plans available | Free tier, Advanced (Google One AI Premium) | --- ## When to Use Each **Choose Gemini if** you live in the Google ecosystem and want AI that integrates naturally with Gmail, Docs, Drive, and Search. NotebookLM and Deep Research are standout features, especially for Google-heavy workflows. The API pricing is also among the most competitive. **Choose Open WebUI if** you want to use Gemini alongside other providers, need persistent knowledge bases, or want to self-host. Open WebUI connects to the Google AI API so you still get Gemini's models. **Use both.** Use Gemini directly for Google Workspace integration and NotebookLM. Connect Open WebUI to the Google AI API for Gemini models alongside Claude, OpenAI, and local models in one interface. --- ## Use Gemini Through Open WebUI Gemini models are available through Open WebUI via the Google AI API. You can use Gemini's multimodal capabilities alongside other models you connect. **How to connect:** 1. Get an API key from [aistudio.google.com](https://aistudio.google.com/) 2. In Open WebUI, go to **Admin → Settings → Connections** 3. Add a new connection with the base URL `https://generativelanguage.googleapis.com/v1beta/openai` and your Google AI API key 4. Gemini models will appear in your model selector > **Tools need extra setup on this endpoint** > > Google's OpenAI compatibility layer uses a different tool-call shape than OpenAI-compatible clients expect, so a tool-using turn can come back as an empty assistant message. This can affect builtin tools such as Memory. Set **Function Calling** to **Legacy** in the model's Advanced Params, or route Gemini through a gateway such as LiteLLM or OpenRouter. See [Blank Replies When the Model Uses a Tool](/troubleshooting/connection-error#-blank-replies-when-the-model-uses-a-tool) and the [OpenAI-compatible provider guide](/getting-started/quick-start/connect-a-provider/starting-with-openai-compatible). --- _Gemini brings strong multimodal AI to the Google ecosystem. Open WebUI is one way to use those models alongside others, on your own infrastructure._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I use Gemini in Open WebUI?** Yes. Add your Google AI API key in Settings and Gemini models appear in the model selector. **Can I self-host Gemini?** Not Gemini itself, but you can use Gemini models through Open WebUI via the Google AI API. Open WebUI runs on your infrastructure, though API calls still go to Google. **Can I use Gemini and Claude together?** Yes, Open WebUI supports connecting to multiple providers at once. --- **Related:** [Open WebUI & ChatGPT](/alternatives/chatgpt) · [Open WebUI & Claude](/alternatives/claude) · [Open WebUI & Ollama](/alternatives/ollama) --- # Open WebUI & Jan Source: https://docs.openwebui.com/alternatives/jan _Last updated: August 2026_ [Jan](https://jan.ai/) by Homebrew (Menlo Research) is built on a clear vision: AI should run on your device, offline, completely under your control. The desktop app is clean, the model hub makes it easy to get started, and the commitment to privacy is genuine. [GitHub](https://github.com/janhq/jan) · [Apache 2.0 License](https://github.com/janhq/jan/blob/main/LICENSE) --- ## What Jan Does Well - **Local-first** with everything running on your machine, 100% offline - **Simple and focused** with a clean interface that avoids unnecessary complexity - **Built-in model hub** for browsing and downloading models with one click - **Cortex engine** powering the runtime with support for GGUF and TensorRT-LLM - **Thread-based conversations** for organizing chats by topic - **Extensions system** for adding capabilities through community plugins - **Open source** under the Apache 2.0 license - **Privacy by design** so your data never leaves your device - **Lightweight** and runs well on modest hardware - **Cross-platform** on macOS, Windows, and Linux --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) for delegated and scheduled work - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Web-based platform** with multi-user access from any browser - **Any model, any provider** using local models alongside OpenAI, Anthropic, Google, and others - **Knowledge & RAG** with persistent knowledge bases and advanced retrieval - **Team features** including Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full computing environment for code execution - **Scales up** from one person to thousands, Docker to Kubernetes --- ## At a Glance | | Open WebUI | Jan | | --- | --- | --- | | Approach | Self-hosted web platform for individuals and teams | Desktop app for private, local AI | | Model management | Connects to model runners and APIs | Built-in model hub with one-click downloads | | Multi-provider | Local + cloud models | Focused on local models | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Focused on chat | | Multi-user | SSO, RBAC, SCIM, teams | Personal desktop use | | Offline | Fully offline with local models | 100% offline | | License | Open WebUI License | Apache 2.0 | --- ## When to Use Each **Choose Jan if** you want the simplest, most private way to run AI locally on your desktop. No servers, no configuration, no accounts. Just download, pick a model, and start chatting. **Choose Open WebUI if** you need web-based access, team collaboration, knowledge bases, or want to combine local models with cloud providers. Open WebUI runs as a web server that your whole team can use. **Use both.** Jan can serve models via its local API. Connect Open WebUI to Jan's API for web-based team access while keeping Jan as your model runner. --- ## Works With Open WebUI Jan can serve models via a local API endpoint. If you're using Jan to manage your local models, you can connect Open WebUI to Jan's API for a web-based experience with multi-user support, knowledge bases, and tools. --- _Jan keeps local AI simple and private. Open WebUI adds a platform layer on top. Different approaches, same belief that AI should run on your hardware._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I use Jan with Open WebUI?** Yes. Jan can serve models via a local API endpoint. Connect Open WebUI to Jan's API for web-based access with team features. **How do Jan and Open WebUI work together?** Jan handles running models locally on your desktop. Open WebUI can add web-based access, knowledge bases, and team features. You can connect Open WebUI to Jan's API and use them together. **Is Jan free?** Yes. Jan is open source under the Apache 2.0 license. --- **Related:** [Open WebUI & Ollama](/alternatives/ollama) · [Open WebUI & LM Studio](/alternatives/lm-studio) · [Open WebUI & llama.cpp](/alternatives/llama-cpp) --- # Open WebUI & LibreChat Source: https://docs.openwebui.com/alternatives/librechat _Last updated: August 2026_ [LibreChat](https://www.librechat.ai/) is one of the projects we genuinely respect in this space. It offers a multi-provider chat experience with strong authentication support, side-by-side model comparison, and a focused feature set that does the fundamentals well. The project is MIT-licensed, actively maintained, and Danny and the community behind it have built something solid. [GitHub](https://github.com/danny-avila/LibreChat) · [MIT License](https://github.com/danny-avila/LibreChat/blob/main/LICENSE) --- ## What LibreChat Does Well - **Multi-provider chat** with a unified interface for OpenAI, Anthropic, Google, Azure, Ollama, and any OpenAI-compatible API - **Model comparison** with side-by-side responses from different models in a single conversation - **Presets system** for saving and quickly switching between model configurations and system prompts - **Artifacts** for rendering code outputs, documents, and visualizations inline - **Authentication** including LDAP, SSO, and social login support - **Built-in code interpreter** for supported models - **Prompt caching** for reducing API costs on repeated interactions - **Focused scope** that does the chat interface well without overcomplicating things - **Active development** with a responsive maintainer and engaged community - **MIT licensed** --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) for delegated and scheduled work - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Platform beyond chat** including Notes, Channels, Automations, Open Terminal, voice/video calls, image generation, and calendar - **Knowledge & RAG** with 13 vector databases, 8 extraction engines, hybrid search with reranking, and agentic retrieval - **Model agents** that wrap any model with custom instructions, tools, knowledge, and parameters - **Enterprise features** including RBAC, SSO/OIDC/LDAP, SCIM 2.0, analytics dashboards, and evaluation arena - **Flexible deployment** via Docker, Kubernetes, pip, or desktop app, with horizontal scaling and OpenTelemetry --- ## At a Glance | | Open WebUI | LibreChat | | --- | --- | --- | | Focus | Full AI platform with knowledge, tools, and team features | Multi-provider AI chat interface | | Multi-provider | Ollama, OpenAI, Anthropic, Google, Azure, Bedrock, and more | OpenAI, Anthropic, Google, Azure, Ollama, and more | | Model comparison | Multi-model chats | Side-by-side comparison | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search, agentic retrieval | File attachment support | | Extensibility | Python tools, MCP, OpenAPI, pipelines | Plugin system with presets | | Code execution | Python in-browser + Open Terminal | Built-in code interpreter | | Team collaboration | Channels, Notes, RBAC, SSO, SCIM | Multi-user with auth | | License | Open WebUI License | MIT | --- ## When to Use Each **Choose LibreChat if** you want a clean, focused multi-provider chat interface with strong model comparison features. The presets system makes it easy to switch between configurations, and the MIT license gives you maximum flexibility. **Choose Open WebUI if** you need a broader platform with knowledge bases, team collaboration tools, Python extensibility, or enterprise features like SCIM and analytics. **Run both.** They connect to the same backends. Some teams use LibreChat for quick individual chats and Open WebUI for collaborative work with knowledge bases and tools. --- ## Use Them Together Both projects connect to the same backends (Ollama, OpenAI, etc.), so you can run both side by side. Some teams use LibreChat for quick individual chats and Open WebUI for team collaboration and knowledge work. --- _Two actively maintained projects making self-hosted AI accessible. Different strengths, same ecosystem._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **How do LibreChat and Open WebUI compare?** LibreChat does the multi-provider chat interface really well. Open WebUI also includes knowledge bases, team collaboration, extensibility, and enterprise features. Different scope, both worth looking at. **Is LibreChat free?** Yes. LibreChat is MIT licensed and free to self-host. **Can I use both LibreChat and Open WebUI?** Yes. Both connect to the same backends (Ollama, OpenAI, etc.), so you can run both side by side. --- **Related:** [Open WebUI & AnythingLLM](/alternatives/anythingllm) · [Open WebUI & Msty](/alternatives/msty) · [Open WebUI & Ollama](/alternatives/ollama) --- # Open WebUI & llama.cpp Source: https://docs.openwebui.com/alternatives/llama-cpp _Last updated: August 2026_ [llama.cpp](https://github.com/ggml-org/llama.cpp) by Georgi Gerganov is one of the most important projects in the AI ecosystem, and we mean that. Without llama.cpp, the local AI movement as we know it wouldn't exist. It proved that you could run serious models on consumer hardware, introduced the GGUF format that became the industry standard, and inspired an entire generation of tools. And with `llama-server`, it's not just an engine anymore: it has its own built-in web interface and OpenAI-compatible API ready to go. [GitHub](https://github.com/ggml-org/llama.cpp) · [MIT License](https://github.com/ggml-org/llama.cpp/blob/main/LICENSE) --- ## What llama.cpp Does Well - **State-of-the-art inference performance** on consumer hardware, consistently pushing what's possible - **Built-in web interface** via `llama-server`, ready to use out of the box - **Broad hardware support** including CPU, CUDA, Metal, Vulkan, and SYCL - **GGUF format** that became the quantized model standard for the entire industry - **Quantization options** from Q2 to Q8 with multiple strategies for different quality/speed tradeoffs - **Speculative decoding** for faster generation using draft models - **Flash Attention** and other advanced inference optimizations - **Grammar-constrained generation** for structured outputs (JSON, code, etc.) - **OpenAI-compatible API** via `llama-server` so any tool can connect to it - **Multi-model router mode** for serving multiple models from one endpoint - **One of the most actively developed projects in AI** with a pace of commits that's hard to match - **MIT licensed** and actively maintained --- ## What Open WebUI Does Well - **Full agentic platform** on top of the models llama.cpp serves, with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Rich web platform** with full chat, conversations, history, organization, and search - **Knowledge & RAG** with 13 vector databases, 8 extraction engines, and hybrid search with reranking - **Multi-provider support** to use llama.cpp models alongside OpenAI, Anthropic, Google, and others - **Team platform** with Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full computing environment for code execution - **Multi-user support** from one person to thousands --- ## When to Use Each **Use llama.cpp directly if** you want maximum control over inference. It gives you fine-grained tuning of quantization, context sizes, batch processing, and hardware utilization that no wrapper can match. The built-in web UI works well for solo use. **Add Open WebUI if** you want a richer interface, knowledge bases, team access, or the ability to connect other providers alongside llama.cpp. Open WebUI talks to `llama-server` via its OpenAI-compatible API. **Use both.** llama.cpp handles inference with maximum performance. Open WebUI handles the platform layer with knowledge, tools, and collaboration. --- ## Use Them Together llama.cpp's `llama-server` exposes an OpenAI-compatible API, which means Open WebUI can connect to it directly. Use llama.cpp for high-performance inference, Open WebUI for the platform layer. ``` # Start llama-server llama-server -m your-model.gguf --port 8081 # Point Open WebUI at it # In Admin → Settings → Connections, add: # URL: http://localhost:8081/v1 ``` --- _llama.cpp made local AI possible. Open WebUI builds a platform layer on top. They work well together._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I connect llama-server to Open WebUI?** Yes. llama-server exposes an OpenAI-compatible API. Add `http://localhost:8081/v1` as a connection in Open WebUI and your models appear automatically. **Does Open WebUI support llama-server's multi-model routing?** Yes. If you're running llama-server in router mode with multiple models, Open WebUI will detect and list all available models through the API. **Is llama.cpp free?** Yes. llama.cpp is MIT licensed and free for any use. --- **Related:** [Open WebUI & Ollama](/alternatives/ollama) · [Open WebUI & LM Studio](/alternatives/lm-studio) · [Open WebUI & Jan](/alternatives/jan) --- # Open WebUI & LM Studio Source: https://docs.openwebui.com/alternatives/lm-studio _Last updated: August 2026_ [LM Studio](https://lmstudio.ai/) has nailed the desktop experience for local AI. The built-in model browser makes discovering and downloading models from Hugging Face effortless, the inference performance is solid, and the UI is clean and intuitive. For anyone who wants to run local models without touching a terminal, LM Studio is a strong option. Proprietary · Free for personal and commercial use --- ## What LM Studio Does Well - **Model browser** for discovering, downloading, and managing models from Hugging Face with a GUI - **Model search and filtering** to find exactly the right model by size, architecture, or quantization - **Quantization preview** so you can see how different quantization levels affect model quality before downloading - **Strong performance** with solid hardware utilization (Metal, CUDA) for fast local inference - **OpenAI-compatible API server** that serves your local models to any application that speaks the OpenAI API - **MCP support** for connecting to Model Context Protocol servers for extended tool use - **RAG capabilities** with built-in document-based chat for local files - **Prompt templates** with a library of pre-configured prompts for common tasks - **Free for everyone** for both personal and commercial use - **Cross-platform** on macOS, Windows, and Linux - **Developer-friendly** local API server for integrating local models into your projects --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations), driving the models LM Studio serves - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Full web platform** with multi-user chat, Notes, Channels, Automations, Open Terminal, and more - **Any provider** so you can use LM Studio's local models alongside OpenAI, Anthropic, Google, and others - **Deep RAG & Knowledge** with 13 vector databases, 8 extraction engines, and hybrid search with reranking - **Team features** including RBAC, SSO/OIDC/LDAP, SCIM 2.0, analytics, and evaluation arena - **Scales from one to thousands** via Docker, Kubernetes, and pip --- ## At a Glance | | Open WebUI | LM Studio | | --- | --- | --- | | Approach | Self-hosted web platform for teams and individuals | Desktop app for local model management and chat | | Model management | Connects to model runners (Ollama, etc.) | Built-in model browser with Hugging Face integration | | Multi-provider | Local + cloud models in one interface | Focused on local models | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Built-in document chat | | Multi-user | SSO, RBAC, SCIM, teams | Personal desktop use | | Extensibility | Python tools, MCP, OpenAPI, pipelines | MCP support | | API server | Full API | OpenAI-compatible local server | | Pricing | Free community edition; Enterprise plans available | Free for personal and commercial use | --- ## When to Use Each **Choose LM Studio if** you want the best desktop experience for discovering and running local models. The model browser makes it easy to explore what's available on Hugging Face, compare quantizations, and get running quickly. **Choose Open WebUI if** you want a web-based platform with team access, persistent knowledge bases, or the ability to use local models alongside cloud providers like OpenAI, Anthropic, and Google. **Use both.** LM Studio's model browser and management are excellent for finding and running models. Open WebUI can connect to LM Studio's API server to add web access, knowledge bases, and team features on top. --- ## Use Them Together LM Studio's OpenAI-compatible API server works well as a backend for Open WebUI. You can use LM Studio to manage and serve your local models, then connect Open WebUI to LM Studio's API. **How to connect:** 1. In LM Studio, start the local API server (default port 1234) 2. In Open WebUI, go to **Admin → Settings → Connections** 3. Add a new OpenAI-compatible connection with URL `http://localhost:1234/v1` 4. Your LM Studio models will appear in the model selector --- _LM Studio makes local models accessible on the desktop. Open WebUI adds a web-based platform layer. Both are making local AI more useful._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I use LM Studio with Open WebUI?** Yes. Start LM Studio's local API server and add `http://localhost:1234/v1` as a connection in Open WebUI. **How do LM Studio and Open WebUI work together?** LM Studio handles model management and local inference on your desktop. Open WebUI can add web-based multi-user access, knowledge bases, and team features. A lot of people use LM Studio as the backend and Open WebUI as the frontend. **Is LM Studio free?** Yes. LM Studio is free for personal and commercial use, though it is proprietary software. --- **Related:** [Open WebUI & Ollama](/alternatives/ollama) · [Open WebUI & llama.cpp](/alternatives/llama-cpp) · [Open WebUI & Jan](/alternatives/jan) --- # Open WebUI & Msty Source: https://docs.openwebui.com/alternatives/msty _Last updated: August 2026_ [Msty](https://msty.app/) has built a refined desktop experience for people who want one place to use both local and cloud-based models. The split-chat feature for running multiple models side-by-side to compare responses is genuinely useful, and the overall design feels thoughtful. Proprietary · Free tier available --- ## What Msty Does Well - **Split chat** for running multiple models side-by-side to compare responses in real time - **Unified hub** for local models (via Ollama, llama.cpp, MLX) and cloud APIs (OpenAI, Anthropic, Google) - **Knowledge Stacks** for uploading documents and chatting with them using built-in RAG - **Offline mode** for fully air-gapped use with local models - **Batch prompting** for sending the same prompt to multiple models simultaneously - **Hardware optimization** with good performance across NVIDIA, AMD, and Apple Silicon - **Persona & Prompt Studios** for creating reusable personas and prompt templates - **Conversation export** in multiple formats for archiving and sharing - **Web search integration** with real-time web search during conversations - **Thoughtful experience** that feels refined and considered - **Free tier** with core features available at no cost --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) for delegated and scheduled work - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Web-based platform** with multi-user access from any browser - **Any model, any provider** connecting to any OpenAI-compatible API, Ollama, or cloud provider - **Deep RAG & Knowledge** with 13 vector databases, 8 extraction engines, and hybrid search with reranking - **Team features** including Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full computing environment for code execution - **Source available** so you can read, audit, and modify the source code --- ## At a Glance | | Open WebUI | Msty | | --- | --- | --- | | Approach | Self-hosted web platform | Desktop app | | Multi-model comparison | Multi-model chats | Split chat with side-by-side responses | | Multi-provider | Any OpenAI-compatible API + Ollama | Local models + cloud APIs | | Knowledge & RAG | 13 vector DBs, 8 extraction engines, hybrid search | Knowledge Stacks with document chat | | Extensibility | Python tools, MCP, OpenAPI, pipelines | Persona & Prompt Studios | | Multi-user | SSO, RBAC, SCIM, teams | Teams plan available | | Source availability | Source available | Proprietary | | Pricing | Free community edition; Enterprise plans available | Free tier, Aurum, and Teams plans | --- ## When to Use Each **Choose Msty if** you want a polished desktop app for personal use, especially if you compare models frequently. The split-chat feature and batch prompting make it easy to evaluate different models side by side. **Choose Open WebUI if** you need a web-based platform, team access, deeper knowledge management, Python extensibility, or enterprise features. Open WebUI runs as a server that your whole team can reach from any browser. **Different form factors.** Msty excels as a desktop app for individual power users. Open WebUI works well as a team platform accessible from anywhere. --- _Msty brings polish to desktop AI. Open WebUI takes a web-based, team-oriented approach. Different tools, same goal of making AI more useful._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **How do Msty and Open WebUI compare?** Msty has a polished desktop experience with a great split-chat feature for comparing models. Open WebUI takes a web-based approach with multi-user support, knowledge bases, and extensibility. Different tools for different preferences. **Is Msty free?** Msty has a free tier. Premium features require a paid Aurum plan. Teams pricing is also available. **Is Msty open source?** No. Msty is proprietary software with a free tier. --- **Related:** [Open WebUI & LM Studio](/alternatives/lm-studio) · [Open WebUI & LibreChat](/alternatives/librechat) · [Open WebUI & Jan](/alternatives/jan) --- # Open WebUI & Ollama Source: https://docs.openwebui.com/alternatives/ollama _Last updated: August 2026_ [Ollama](https://ollama.com/) is the project that made local AI click for millions of people, and Open WebUI wouldn't be where it is without them. One command to install, one command to run, and you're chatting with a model. The desktop app includes a built-in chat interface, the CLI is fast and intuitive, and the team behind it consistently ships. We're big fans. [GitHub](https://github.com/ollama/ollama) · [MIT License](https://github.com/ollama/ollama/blob/main/LICENSE) --- ## What Ollama Does Well - **Dead simple** to install and run a model in seconds - **Desktop app with built-in chat** for a complete standalone experience - **Huge model library** with hundreds of models ready to download from the Ollama registry - **Modelfiles** for customizing models with system prompts, parameters, and adapters - **Great performance** optimized for consumer hardware (Metal, CUDA, CPU) with automatic GPU layer splitting - **OpenAI-compatible API** that works as a backend for many tools and applications - **Concurrent model loading** for running multiple models simultaneously - **Cross-platform** on macOS, Linux, Windows, and Docker - **Actively developed** with fast iteration and a responsive team - **MIT licensed** --- ## What Open WebUI Does Well - **Full agentic platform** on top of your local models, with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Rich web interface** with full chat, conversations, history, search, and organization - **Knowledge & RAG** with 13 vector DBs, 8 extraction engines, and hybrid search - **Multi-provider support** so you can use Ollama alongside OpenAI, Anthropic, Google, and others - **Team platform** with Channels, Notes, Automations, RBAC, SSO/OIDC/LDAP, and SCIM 2.0 - **Open Terminal** providing a full sandboxed computing environment for code execution - **Model agents** with custom instructions, bound tools, and knowledge per model --- ## Better Together Ollama and Open WebUI are the most popular pairing in the local AI ecosystem. Ollama manages and serves your models; Open WebUI adds a web-based platform with knowledge management, team features, and extensibility on top. ``` # The most common Open WebUI setup ollama pull muse-glimmer:30b-q4_K_M 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 ``` Open WebUI auto-detects Ollama when running on the same machine. All your Ollama models show up in the model selector immediately, no configuration needed. --- ## When to Use Each **Use Ollama if** you want the fastest path to running a model locally. The CLI and desktop app work great on their own for quick interactions, scripting, and development. **Add Open WebUI if** you want a web-based interface with knowledge bases, team features, persistent conversations, or the ability to connect cloud providers alongside your local models. **Most people use both.** Ollama handles the model layer. Open WebUI handles the platform layer. They auto-detect each other and just work. --- ## Other Great Ollama Frontends Ollama's OpenAI-compatible API means it works with many tools. If Open WebUI isn't your style, other projects that pair well with Ollama include: - [**LibreChat**](/alternatives/librechat) for multi-provider chat with model comparison - [**AnythingLLM**](/alternatives/anythingllm) for workspace-based document Q&A --- _Ollama made local AI simple. Open WebUI builds on that foundation. Together, they've helped millions of people run AI on their own hardware._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **Can I use Ollama with Open WebUI?** Yes. Open WebUI has native Ollama integration and auto-detects it when running on the same machine. No configuration needed. **Is Ollama free?** Yes. Ollama is MIT licensed and free for personal and commercial use. **How do Ollama and Open WebUI work together?** Ollama handles running and managing models. Open WebUI can serve as the web interface and also has things like knowledge bases, team features, and extensibility. Most people use them together. **Do I need Ollama to use Open WebUI?** No. Open WebUI works with any OpenAI-compatible API, including llama.cpp, LM Studio, OpenAI, Anthropic, Google, and more. Ollama is a popular option, but not required. --- **Related:** [Open WebUI & llama.cpp](/alternatives/llama-cpp) · [Open WebUI & LM Studio](/alternatives/lm-studio) · [Open WebUI & Jan](/alternatives/jan) --- # Open WebUI & Onyx Source: https://docs.openwebui.com/alternatives/onyx _Last updated: August 2026_ [Onyx](https://onyx.app/) (formerly Danswer) focuses on a specific and important problem: connecting AI to your organization's internal knowledge across Slack, Google Drive, Confluence, Jira, GitHub, and dozens of other tools, with permission-aware retrieval. If your team's knowledge is scattered across many tools and you need AI to search across all of them while respecting access controls, that's Onyx's sweet spot. > **How to check this page** > > Everything claimed here about Open WebUI is verifiable in our own documentation, linked throughout. Everything about Onyx comes from Onyx's own documentation, repository and licence terms, all linked below, and describes their project as of the date above. Onyx ships quickly, so treat anything undated as possibly out of date and check their sources before deciding. > > > > If something here is wrong or has aged badly, including in Onyx's favour, [tell us](https://github.com/open-webui/docs/issues) and we will correct it. [GitHub](https://github.com/onyx-dot-app/onyx) · [Source Available](https://github.com/onyx-dot-app/onyx/blob/main/LICENSE) (MIT core + Onyx Enterprise License for `ee/` directories) · [Self-Host Terms](https://onyx.app/legal/self-host) --- ## What Onyx Does Well - **Enterprise connectors**, [40+ by Onyx's count](https://docs.onyx.app/connectors/overview), with native integrations for Slack, Google Drive, Confluence, Jira, GitHub, Notion, and more - **Automatic syncing** that keeps connected sources up to date without manual re-ingestion - **Permission-aware retrieval** that respects source system access controls when returning search results - **Enterprise search** purpose-built for searching across your organization's internal knowledge - **Multi-surface access** via web app, Slack bot, Discord bot, Chrome extension, and CLI - **Managed cloud option** for teams that don't want to self-host - **Custom agents with actions** for building AI assistants that can take actions across connected tools - **Active development** with frequent releases and community responsiveness --- ## What Open WebUI Does Well - **Full agentic platform** with [builtin tools](/features/extensibility/plugin/tools#built-in-system-tools-nativeagentic-mode) the model calls itself, [MCP](/features/extensibility/mcp) servers, [sub-agents](/features/chat-conversations/chat-features/subagents), [timers](/features/chat-conversations/chat-features/timers) and [automations](/features/chat-conversations/chat-features/automations) for delegated and scheduled work - **Customise practically everything**, from per-model prompts, tools, knowledge and parameters to [filters, pipes, actions and event functions](/features/extensibility/plugin/functions) that change behaviour anywhere in the pipeline, plus theming, banners and per-group permissions - **Full AI platform** with Chat, Notes, Channels, Automations, Open Terminal, voice/video calls, and image generation - **Cloud storage in chat** with Google Drive, OneDrive (personal and business) and SharePoint file pickers - **Deploy anywhere** on your own infrastructure, fully air-gapped if needed - **Free community edition** with unlimited users, OIDC/OAuth SSO, LDAP, RBAC, and SCIM 2.0 included - **Any model, any provider** including Ollama, OpenAI, Anthropic, Google, Azure, Bedrock, and any OpenAI-compatible API - **Knowledge & RAG** with 13 vector databases, 8 content extraction engines, and hybrid BM25 + vector search with cross-encoder reranking --- ## Licensing and Paid Tiers Both projects are free to self-host and both sell paid tiers. They place different capabilities in different tiers, so the practical question is which feature set matches the deployment you are planning. **Open WebUI** is source available under the [Open WebUI License](https://github.com/open-webui/open-webui/blob/main/LICENSE), a BSD-3 clause licence with one addition: you may not remove or replace Open WebUI branding once a deployment exceeds 50 users in a rolling 30 day period, unless you hold an enterprise licence. **Onyx** licenses its Community Edition core under MIT, covering chat, RAG, agents and actions. That grant is not repository-wide: Onyx's own [LICENSE](https://github.com/onyx-dot-app/onyx/blob/main/LICENSE) carves out everything under `ee` directories and places it under the Onyx Enterprise License instead. Taken on its own, MIT is a more permissive licence than ours, and that matters if you intend to redistribute or fork the core. ### What each free self-hosted edition includes Open WebUI's free edition against Onyx's Community Edition, the part carrying the MIT licence. Onyx's column follows its [Enterprise Edition](https://docs.onyx.app/deployment/miscellaneous/enterprise_edition) and [access control](https://docs.onyx.app/security/architecture/access_controls) documentation, and the per-tier gating in its own `license_enforcement_config.py`. Onyx's paid tiers are available self-hosted as well as on its cloud, so "Business" and "Enterprise" below can still mean self-hosted. | Capability | Open WebUI (free) | Onyx Community Edition (free) | | --- | --- | --- | | OIDC / OAuth single sign-on | Included | Enterprise Edition | | SAML single sign-on | Via a trusted-header proxy that terminates SAML | Enterprise Edition native support | | LDAP / Active Directory | Included | Not documented | | User groups and role-based access control | Included | Business tier or above | | Per-resource access grants (users and groups) | Included | Business tier or above | | SCIM 2.0 provisioning | Included | Enterprise tier | | Audit logging | Included | Not documented | | User limit before paying | None | None | | Giving different teams access to different documents | Separate knowledge bases, each granted to the users or groups you choose | Enterprise Edition | | Different access to individual files inside one collection | Access applies to a knowledge base as a whole | Enterprise Edition | | Permissions mirrored automatically from Slack, Drive or Confluence | Not a current Open WebUI feature | Enterprise Edition | | Removing product branding | Up to 50 users; enterprise licence beyond that | Enterprise Edition | | Dedicated support and SLAs | Enterprise licence | Enterprise Edition | | Priority on feature requests | Enterprise licence | Enterprise Edition | Nothing marked Included in Open WebUI's column needs a licence key, a seat count or a paid plan. They are configurable settings. Two rows deserve care, because the distinction is easy to blur. Open WebUI gives separate teams access to separate document sets by putting them in different knowledge bases and granting each to the right groups. Onyx's paid editions go deeper for enterprise search: they can mirror source-system permissions from tools like Slack, Drive and Confluence and enforce them during retrieval. If your documents already have complex permissions in those source systems, that is a real strength of Onyx. Dedicated support and priority on the roadmap are paid on both sides, which is how each project is funded, and neither pretends otherwise. On [Onyx Cloud](https://onyx.app/pricing) as of July 2026, the Business tier is $20 per user per month and buys role-based access control and permission inheritance, but not single sign-on, SCIM or outbound webhooks. Those are Enterprise, which is a contact-us. So the summary is this. If you are self-hosting and need managed identity in the free edition, Open WebUI includes it for any number of users. If you need per-document permissions mirrored from Slack or Drive, Onyx is designed for that in its paid editions. If you intend to fork or redistribute, Onyx's core carries the more permissive licence. > **Check both before you decide** > > Pricing and tiers change. These figures come from each project's own published terms on the date at the top of this page. Verify against [Onyx's pricing](https://onyx.app/pricing) and our [licence](https://github.com/open-webui/open-webui/blob/main/LICENSE) rather than trusting either vendor's summary, including this one. --- ## At a Glance | | Open WebUI | Onyx | | --- | --- | --- | | Primary focus | General-purpose AI platform | Enterprise search and knowledge discovery | | Knowledge approach | Document upload, knowledge bases, 13 vector DBs, 8 extraction engines | 40+ enterprise connectors with automatic syncing | | Permission handling | Groups, roles and per-resource access grants, in the free edition | Permission-aware retrieval mirrored from source systems, on the paid tiers | | Multi-provider | Any OpenAI-compatible API + Ollama | Multiple LLM provider support | | Extensibility | Python tools, MCP, OpenAPI, pipelines | Focused on connector and search ecosystem | | Collaboration | Channels, Notes, shared conversations | AI-powered search and Q&A | | License | Open WebUI License (BSD-3 plus a branding clause above 50 users) | MIT for the Community Edition core; separate terms for Enterprise features, see self-host terms | For which identity and access features each free edition includes, see [the table above](#what-each-free-self-hosted-edition-includes) rather than this summary. --- ## When to Use Each **Choose Onyx if** you want to connect AI to your organization's existing tools. If your team's knowledge lives in Slack, Confluence, Jira, Google Drive, and GitHub, Onyx's 40+ connectors with automatic syncing and permission-aware retrieval were built for that. Two parts of that are worth being precise about, because they are areas where Onyx has a purpose-built model: - **Continuous sync into the knowledge base.** Open WebUI connects to cloud storage at the point of use: users can pull files from [Google Drive](/features/chat-conversations/rag#google-drive-integration), OneDrive and SharePoint straight into a chat. Knowledge bases are populated by upload, by directory sync or through the API, and [oikb](/ecosystem/knowledge-base-sync) extends that to repositories, buckets and wikis on a schedule. Onyx builds continuous connector sync directly into the product. - **Permission inheritance from the source system.** Open WebUI grants access per knowledge base, so you separate what different teams may read by putting it in different knowledge bases. Onyx can mirror a source system's access control list and enforce it at retrieval time, on its Enterprise Edition. If you are indexing a large shared Drive whose permissions already encode who may see what, that difference is the whole decision. If either is a hard requirement, Onyx is the better fit. Note that both are [Enterprise Edition features](https://docs.onyx.app/deployment/miscellaneous/enterprise_edition) on Onyx's side, so the comparison to make is against a paid Onyx deployment rather than the free Community Edition. **Choose Open WebUI if** you need a general-purpose AI platform with chat, knowledge bases, team collaboration, Python extensibility, and support for any model provider. Open WebUI includes SSO, LDAP, RBAC, SCIM 2.0 and audit logging in the free community edition, for unlimited users, which is the deciding factor for organisations that need managed identity without a per-seat contract. **They solve different problems.** Onyx excels at enterprise search and connecting AI to your existing tools. Open WebUI excels as a general AI platform. Many organizations could use both. --- _Onyx connects AI to your enterprise knowledge. Open WebUI comes at it from a more general angle. They solve different problems, and many organizations could benefit from both._ **Ready to try Open WebUI?** [Get started →](/getting-started) --- ## Frequently Asked Questions **How do Onyx and Open WebUI compare?** Onyx leans into enterprise search with 40+ connectors and permission-aware retrieval. Open WebUI comes at it from a more general angle with chat, knowledge bases, team collaboration, and extensibility. Different tools for different needs. **Is Onyx open source?** Partly. Onyx's Community Edition core is MIT licensed, and everything under its `ee` directories is excluded from that grant and carries separate enterprise terms. Additional [self-host terms](https://onyx.app/legal/self-host) may also apply. Note that the licence and the price are separate questions: MIT covers the core, while single sign-on and access control sit in Onyx's paid tiers. For redistribution specifically, MIT on that core is more permissive than the Open WebUI License. **How do SSO and RBAC compare?** Open WebUI includes OIDC and OAuth single sign-on, LDAP, RBAC, SCIM 2.0 provisioning and audit logging in the free edition, for unlimited users, with no licence key. In Onyx, [user groups, RBAC and SSO are paid-tier features](https://docs.onyx.app/deployment/miscellaneous/enterprise_edition) for self-hosted deployments. On Onyx Cloud, RBAC starts at the Business tier and SSO at the Enterprise tier. **Is Onyx free?** The community edition is free to self-host. Additional [self-host terms](https://onyx.app/legal/self-host) may apply. Onyx Cloud and Enterprise plans are available for teams that want managed hosting or additional features. **Can I use both Onyx and Open WebUI?** Yes. They solve different problems. Onyx connects AI to your existing enterprise tools. Open WebUI also has knowledge management, team features, and extensibility built in. **Which is better for enterprise AI deployment?** It depends on your needs. If your priority is searching across internal tools with permission-aware retrieval, Onyx was built for that. If you need more of a general-purpose AI platform that you can deploy on your own infrastructure, with SSO, RBAC, and SCIM included in the free edition, that is more where Open WebUI fits. --- **Related:** [Open WebUI & Dify](/alternatives/dify) · [Open WebUI & AnythingLLM](/alternatives/anythingllm) · [Open WebUI & LibreChat](/alternatives/librechat) --- # Open WebUI Design Guidelines ![Open WebUI Brand Guidelines: official assets, correct naming, clear space, and usage rules](/images/banners/brand-light.svg)![Open WebUI Brand Guidelines: official assets, correct naming, clear space, and usage rules](/images/banners/brand-dark.svg) Source: https://docs.openwebui.com/brand Welcome to the Open WebUI design guidelines. This document provides the essential rules and recommendations to ensure consistent and clear use of the Open WebUI brand assets. ## Brand Assets The following are the official Open WebUI brand assets. These assets are provided for approved use in documentation, integrations, and community materials. ### Icon ![Open WebUI icon](/images/open-webui-icon.png) - Primary Open WebUI icon - Preferred for app icons, favicons, avatars, social profiles, launchers, integrations, and compact brand placements - Use the icon when the Open WebUI name appears nearby in surrounding text or UI - Maintain adequate clear space around the icon - Do not modify, recolor, crop, stretch, or add effects [Download Icon](/assets/files/open-webui-icon-115aa34b938cd4b21063a0a1da4c06e0.png) ### Horizontal Logo ![Open WebUI horizontal logo](/images/open-webui-wordmark.png) - Official Open WebUI horizontal logo - Use when the icon needs to appear with the Open WebUI name in the same asset - Use on light, clean backgrounds for best legibility - Maintain adequate clear space around the logo - Do not modify, recolor, crop, stretch, or add effects [Download Horizontal Logo](/assets/files/open-webui-wordmark-73058ed4a1e3f102e4d28c9fcdbc2cc6.png) ### Logo Asset ![Open WebUI logo asset](/images/open-webui-logo.png) - Official Open WebUI logo asset - Use for existing materials and placements that already rely on this logo file - Prefer the icon or horizontal logo for new brand placements - Do not modify, recolor, crop, stretch, or add effects [Download Logo Asset](/assets/files/open-webui-logo-a5024b13d950315f75cf406700bbd404.png) [Download Transparent Logo Asset](/assets/files/open-webui-logo-transparent-9665c5e6fe8abe6bfab2ba83db0c409a.png) ### Asset Source - Official brand assets are available in the project repository - Always use the provided files rather than recreating assets manually - If an asset is missing or a different format is required, contact the Open WebUI team through official project channels ## Brand Name Usage The official name is **Open WebUI**. ### Correct Usage: - Open WebUI (when referring to the brand or product) - open-webui (typically used for repository or package names) ### Incorrect Variations (Do NOT use): - OpenWeb UI - OpenWebUI - OpenWeb - Open Web UI - openweb-ui - OpenWeb Ui - openWebUI - Open-Web UI - open web UI - open-ui - open-web-ui Always use **Open WebUI** as two separate words with capitalization as shown when referring to the brand or product. When referring to the repository, package, or codebase, use **open-webui** in lowercase with hyphens. ## Logo and Visual Identity - Prefer the Open WebUI icon for compact brand placements. - Use the horizontal logo only when the brand name needs to be included in the asset. - Use the Open WebUI icon and horizontal logo as provided without modifications. - Do NOT stretch, crop, or distort the icon or logo. - Do NOT change the brand asset colors or add effects. - Provide clear space around brand assets to maintain visibility. - Use brand assets on clean, uncluttered backgrounds to ensure legibility. ## Typography - Use simple, readable fonts consistent with web standards. - Use consistent font sizes and styles across all Open WebUI materials. - Avoid decorative fonts that reduce readability. ## Usage Rules - Do NOT use the Open WebUI logo or name in any way that implies endorsement unless explicitly permitted. - Do NOT incorporate the Open WebUI brand into your own product or company branding. - Maintain clear and proportional spacing when pairing Open WebUI visuals alongside other brand logos. - Always respect brand integrity and use the assets as provided. ## Contact For questions about usage or to request permission for other uses, please contact the Open WebUI team via the official repository or project communication channels. --- Thank you for helping maintain a consistent and clear brand identity for Open WebUI. --- # Contributing Source: https://docs.openwebui.com/contributing **Help build the AI interface everyone deserves.** Open WebUI is an independent project built and maintained by a small, dedicated core team. The most valuable contributions are often not code. Testing dev builds, filing clear bug reports, proposing ideas in Discussions, improving docs, and translating the UI all have an outsized impact on the project. This page explains how to get involved and what to expect. --- ## Code of Conduct All contributors and community participants must follow the **[Code of Conduct](https://github.com/open-webui/open-webui/blob/main/CODE_OF_CONDUCT.md)**. We operate under a **zero-tolerance policy**: disrespectful, demanding, or hostile behavior results in immediate action without prior warning. Open WebUI is led by a small core team and supported by contributors across the project. Treat every interaction with professionalism and respect. --- ## Ways to Contribute ### Test the development branch One of the most valuable contributions requires no code at all. Run the dev branch, use it daily, and report what breaks. ``` docker run -d -p 3000:8080 -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:dev ``` The dev branch moves fast, so **pull updates regularly**. If Docker is not your preference, follow the [Developing Open WebUI](/getting-started/advanced-topics/development) instead. Report issues on [GitHub](https://github.com/open-webui/open-webui/issues) with clear reproduction steps. Community testing helps us deliver high-quality releases. ### Submit code The most impactful way to contribute is through well-written bug reports, detailed feature discussions, and thoughtful ideas posted in [Discussions](https://github.com/open-webui/open-webui/discussions/new/choose). These directly shape the project's direction. If you do submit a pull request, please understand that Open WebUI is held to the highest standard of code quality, consistency, and architectural coherence. Every line merged becomes something the core team must own, maintain, and support indefinitely. For this reason, submitted code may be refactored, rewritten, or used as inspiration for a different implementation. This is not a reflection of your work's quality. It is how we ensure that a small team can deeply understand and evolve every part of the codebase. Before submitting a PR: 1. **Open a discussion first.** Propose your idea [here](https://github.com/open-webui/open-webui/discussions/new/choose) so the team can align on approach before you write code. 2. **Follow existing conventions.** Match the project's coding standards, naming patterns, and architecture. 3. **Keep PRs atomic.** Each pull request should address a single objective. If scope grows, split it into smaller, logically independent PRs. 4. **Avoid new external dependencies.** Do not add libraries or frameworks without prior discussion. We aim to stay framework-agnostic and implement functionality ourselves when practical. 5. **Include tests.** Cover new features with tests and update documentation as needed. 6. **Write clear commit messages.** Descriptive messages make review and history tracking easier. ### Improve documentation Help make Open WebUI more accessible by improving docs, writing tutorials, or creating setup guides. Documentation lives in the [docs repository](https://github.com/open-webui/docs). ### Translate the UI Open WebUI uses JSON translation files in `src/lib/i18n/locales`. Each subdirectory is named with an [ISO 639 language code](http://www.lingoes.net/en/translator/langcode.htm) (e.g., `en-US`, `fr-FR`). To add a new language: 1. Create a new directory under `src/lib/i18n/locales` named with the appropriate language code 2. Copy the `en-US` translation files into the new directory 3. Translate the string values in each JSON file while preserving the object structure 4. Register the language in `src/lib/i18n/locales/languages.json` ### Improve accessibility Accessibility is a core part of good design. When contributing UI changes: | Principle | What to do | | --- | --- | | Semantic HTML | Use