Open WebUI vs LobeHub: Which self-hosted AI interface fits your team?

Open WebUI and LobeHub are the two most downloaded open-source AI interfaces for self-hosted teams. They share fundamentals: both are free, self-hosted, and work with local models or cloud APIs.

But their design philosophies split sharply.

Open WebUI is model-centric. You manage multiple LLMs—via Ollama locally, or APIs like OpenAI, Anthropic, Groq. You tweak inference parameters (temperature, top-p, token limits). You upload documents and search them privately. You control who accesses what via role-based permissions. Built for teams running a shared model cockpit.

LobeHub is agent-centric. You design reusable AI agents with names and personalities. You discover and import pre-built agents from a marketplace of 10,000+. You schedule agents to run on timers. You compose multi-agent teams that collaborate. You get native mobile apps and voice support. Built for teams that think in terms of discoverable, persistent AI actors.

Choose Open WebUI if:

• You run models locally via Ollama and need a shared UI for your team
• You tweak inference settings (temperature, sampling, token limits) regularly
• You upload documents, PDFs, or web links and want to search them privately (RAG)
• Your team needs role-based access control and admin dashboards
• You use multiple LLM providers (OpenAI one day, Anthropic the next, Groq the next) and want one interface for all
• You want enterprise features: LDAP, SSO, OAuth, SCIM provisioning
• You value administrative control and clear governance over a polished interface

Choose LobeHub if:

• You design and reuse AI agents as first-class work objects ("Marketing Agent," "Code Reviewer Agent")
• You want to discover and import 10,000+ pre-built agents from a marketplace
• Your team uses voice chat with the AI (TTS/STT features)
• You need native iOS and Android apps, not just web access
• You juggle multiple LLM providers and want seamless provider-switching built-in
• You prioritize a sleek, modern interface over maximum feature breadth
• You want to schedule agent tasks to run on timers (e.g., "scan for news every morning")
• You like the idea of agents learning from conversation history (memory system)

Ollama: Open WebUI's native bond

Ollama is a package manager for LLMs. Download Llama 2, Mistral, or any open-source model and run it locally on your GPU. Open WebUI is built to wrap Ollama: pull models from Ollama's library directly into chat, expose all inference parameters, and get a team interface.

LobeHub can talk to Ollama, but it is not the design center. LobeHub optimizes for cloud APIs (OpenAI, Claude, Gemini, Bedrock) and the ability to swap providers mid-conversation. If your architecture centers on local models, Open WebUI fits tighter.

Interface design

LobeHub was built for polish. Modern typography, smooth interactions, a refined visual language. Day-to-day comfort matters if your team lives in this tool.

Open WebUI was built for breadth. More options, more panels, more configuration. Some teams call this "comprehensive." Others call it "overloaded." Your preference is legitimate either way.

Team governance vs. agent discovery

Open WebUI assumes an admin controls the portal: which models are available, what tools people can call, what data they can access. Permissions are role-based. Good for enterprises.

LobeHub assumes agents are discoverable shared work objects. Your team finds, uses, and improves agents together. Fewer admin controls, more collaborative iteration. Good for smaller, autonomous teams.

Adoption and momentum

Open WebUI: 154.2K GitHub stars. Gained 2,667 stars in the past 30 days (1.8% growth). 18,717 total commits.

LobeHub: 83.1K GitHub stars. Gained 721 stars in the past 30 days (0.9% growth). 14,512 total commits.

Open WebUI has nearly 2x the star count and is growing 3.7x faster. Both are actively maintained (commits within hours). Open WebUI shows stronger adoption, but LobeHub is thriving.

Self-hosted: both are free

Neither product charges licensing fees. You pay only for: (1) your server or GPU hardware, or (2) cloud API calls if you use OpenAI, Anthropic, etc.

Open WebUI has no SaaS tier. Self-hosting is your only path.

LobeHub offers a cloud SaaS tier (Free, Starter, Premium, Ultimate) with monthly model credits, storage, team features, and task scheduling. The self-hosted community edition runs the same code; commercial features live in the cloud tier. You can also self-host on your own infrastructure at zero cost.

Deployment

Both deploy via Docker. Both run on Kubernetes. Both support multiple databases (Open WebUI: SQLite, PostgreSQL with optional S3/Cloud Storage; LobeHub: database details lighter but less flexible for large teams).

Open WebUI requires more setup if you want to use it across a team: user accounts, permissions, model routing, admin dashboards.

LobeHub requires less initial configuration but expects you to understand agent definitions to maximize value.

Budget for a team of 10

Hardware: EUR 30-100/month (VPS or GPU server). API costs: Depends on LLM provider (OpenAI, Anthropic, etc.). Could be EUR 50-500/month depending on usage. Opsily managed hosting (if you choose): Flat fee for operations, backups, monitoring.

Both tools are cost-neutral. The real expense is compute and LLM inference.

What transfers

API keys (OpenAI, Anthropic, Groq, etc.) are portable. Just re-enter them in the new tool.

Local models via Ollama are independent. Either tool can use them.

What does not transfer

Chat history is stored locally to each tool. Export conversations if you want a record, but do not expect import into the other.

Custom prompt templates, system instructions, and workflow configurations need rebuilding.

Document uploads and RAG training require re-uploading. Vector embeddings are tool-specific.

Team accounts, permissions, and user roles are redefined in the new system.

Effort

Switching effort: 4-8 hours for a team of 10 if you have customizations. 1-2 hours if you are starting with minimal configuration. Both are open-source, so no data lock-in or licensing friction.