Open WebUI is the self-hosted AI chat interface to install. It scores 4.7/5. The documented Docker install is one container with one data volume. It talks to Ollama and to any OpenAI-compatible API, and its user controls go furthest of the three: roles, groups, single sign-on (SSO) and two-factor sign-in.
Pick AnythingLLM if you want the interface to run models itself. It is also one container, and it has a built-in engine for local models on NVIDIA, AMD and Intel graphics cards. Pick LibreChat if your team mostly uses cloud models and you can run five services to get native connections to Anthropic, AWS Bedrock, Azure, Google and OpenAI.
Our picks
- Best overall Open WebUI 4.7 /5
- Best with a built-in model engine AnythingLLM 4.4 /5
- Best for cloud model providers LibreChat 3.2 /5
Scores
1–5 per criterion · total is the weighted average · select a score to see its source| # | Product | Services to run ×3 | Model providers ×3 | Users and sign-in ×2 | Chat with your documents ×2 | Total |
|---|---|---|---|---|---|---|
| 1 | Open WebUI | 5 | 4 | 5 | 5 | 4.7 |
| 2 | AnythingLLM | 5 | 5 | 3 | 4 | 4.4 |
| 3 | LibreChat | 1 | 5 | 4 | 3 | 3.2 |
How each criterion is scored
Services to run ×3
How many containers or services the project's documented standard install starts, counting the app itself and any database, search engine or document service it needs.
- 5 One container or one package, with storage built in
- 4 Two containers or services, such as the app plus one database
- 3 Three containers or services
- 2 Four containers or services
- 1 Five or more containers or services
Model providers ×3
Which AI model sources the interface can connect to: local runners such as Ollama, any OpenAI-compatible API, and named cloud providers with their own built-in support.
- 5 As 4, with ten or more named providers listed in the documentation
- 4 As 3, plus at least two named cloud providers, such as OpenAI and Anthropic
- 3 Ollama plus any OpenAI-compatible API
- 2 Either local runners only or one cloud provider plus OpenAI-compatible APIs
- 1 One provider only
Users and sign-in ×2
Accounts and access controls for running one instance for several people: separate users, roles or permissions, single sign-on (OAuth, OIDC) or LDAP directory sign-in, groups, two-factor sign-in and automatic user provisioning (SCIM).
- 5 As 4, plus user groups and either two-factor sign-in or SCIM provisioning
- 4 As 3, plus single sign-on (OAuth or OIDC) or LDAP sign-in
- 3 Several users with roles or per-user permissions
- 2 Several users with password sign-in, without roles or permissions
- 1 Single user, no sign-in
Chat with your documents ×2
Built-in document search (retrieval-augmented generation, or RAG): whether you can upload files or build knowledge bases the AI searches, whether that needs an extra service, and how many search backends you can choose.
- 5 As 4, plus a choice of several vector databases and either hybrid search or several document extraction engines
- 4 Built-in document search with knowledge bases or workspaces, no extra service needed
- 3 Document search that runs as a separate service
- 2 Files can be attached to a single chat only
- 1 No document upload
Open WebUI is the low-upkeep choice. A single docker run command
starts it, with its data in one volume, so there is one container to
update and one volume to back up. The standard image already
includes the local AI dependencies; a slim image moves embeddings,
document extraction and voice to outside services if you want a
smaller container.
It is also the most complete for a shared install. The project says it is “multi-user from day one”, and the feature list covers roles, groups, per-resource permissions and sign-in through your existing identity provider. Document chat is built in, with hybrid search that combines keyword and vector search. The one limit to know about is the license, which requires preserving the Open WebUI branding.
- One Docker container, or a pip package if you have Python 3.12
- Roles, groups, SSO through OIDC or LDAP, automatic user provisioning (SCIM) and two-factor sign-in
- Knowledge bases with 13 vector database options, hybrid search and 8 document extraction engines
- Names fewer cloud providers than the other two; most connect through an OpenAI-compatible API
- Its license requires keeping the Open WebUI branding
Skip it if: Anyone who wants to put their own brand on the interface.
AnythingLLM is built around chatting with your documents. The Docker image includes a LanceDB vector database by default, so uploads of PDF, TXT and DOCX files work without a second service, and answers come with source citations. You can swap in one of eight other vector databases, such as PGVector or Qdrant. Its built-in engine runs local models with no extra setup, so you don’t need Ollama next to it.
Check two defaults. Multi-user support exists only in the Docker
version; the desktop app is single-user. And the README says it
“contains a telemetry feature that collects anonymous usage
information”. It is on until you set DISABLE_TELEMETRY to true or
switch it off under Privacy in the sidebar.
- One Docker image with a built-in LanceDB vector database
- Runs local models itself on CPU or GPU (NVIDIA through CUDA, AMD and Intel through Vulkan)
- More than 30 named model providers in its README
- Several users and password protection only in the Docker version, not the desktop app
- Sends anonymous usage telemetry until you turn it off
Skip it if: Anyone who needs SSO or LDAP sign-in, which the AnythingLLM pages we read don't mention.
LibreChat has the widest native provider support of the three. Beyond the big cloud APIs it lists Ollama, Mistral AI, Cohere, groq and more, and any OpenAI-compatible API works “no proxy required”. Sign-in supports OAuth2 and LDAP, and a browser-based admin panel manages users, groups and roles.
The cost is upkeep. The default Docker Compose file starts MongoDB, Meilisearch, the RAG API (retrieval-augmented generation, its document search service) and a PostgreSQL database next to LibreChat, and the documentation suggests giving Docker at least 2 GB of memory. Document search depends on two of those services. That is five things to update, and the README warns about breaking changes between versions.
- Native support for Anthropic, AWS Bedrock, OpenAI, Azure OpenAI, Google and Vertex AI
- OAuth2, LDAP and email sign-in, with an admin panel for users, groups and roles
- Imports conversations from ChatGPT and exports them as markdown, text or JSON
- The default Docker Compose setup runs five services
- Its MongoDB image needs a processor with AVX instructions
- The project asks you to check the changelog for breaking changes before every update
Skip it if: Anyone running on an old processor or virtual machine without AVX support.
Questions
Do these work with Ollama?
Yes. Open WebUI connects to local models through Ollama, LibreChat lists Ollama among its local providers, and AnythingLLM lists Ollama and also has its own built-in engine for local models.
Which one is easiest to run on a small server?
Open WebUI or AnythingLLM, since each is one container. AnythingLLM’s Docker guide recommends at least 2GB of RAM on cloud servers. LibreChat runs five services by default and suggests at least 2 GB of memory for Docker. The Open WebUI pages we read give no memory figure.
Can several people share one install?
With all three, but they differ. Open WebUI and LibreChat both support groups and sign-in through LDAP or an identity provider. AnythingLLM supports several users with permissions in its Docker version only.
Method
Each interface was scored 1–5 against a published scale on four weighted criteria: services to run (×3), model providers (×3), users and sign-in (×2) and chat with your documents (×2). The ranking is the weighted average. Every score cites quotes from the project’s own README, documentation or GitHub data, captured on 5 November 2026.
We did not install or benchmark the interfaces, so scores reflect what each project documents. Where a feature is missing from the pages we captured, the score says so. How our rankings work.