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To connect Ollama to Open WebUI, configure an Ollama address that the Open WebUI backend can reach, then select an available model in a new chat. The right address depends on where each application runs: localhost inside a container usually means that container, not your computer. Running a model locally can keep prompts from going to Ollama, but it does not automatically make every part of an Open WebUI setup private.
Choose the right Ollama address for your deployment
Open WebUI makes requests to Ollama from its backend. Use an endpoint reachable from that backend, not simply one that works in a browser or shell on another machine. The official Open WebUI documentation points administrators to the Connections area for managing an Ollama instance and its models; exact labels may vary by release. See the Open WebUI quick start and its Ollama provider guide.
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| Where the services run | Address to consider | Important qualification |
|---|---|---|
| Both run directly on the same host | http://localhost:11434 |
Use this only when Open WebUI’s backend shares the host network context with Ollama. |
| Open WebUI runs in Docker; Ollama runs on the host | http://host.docker.internal:11434 |
This is the documented example; availability and networking behavior can depend on the platform and Docker setup. |
| Both run as services in Docker | Use the Ollama service name and port on their shared Docker network | Container-to-container access normally uses the service name, not a host loopback address. |
| Ollama runs on another machine | Use that server’s reachable internal or otherwise secured hostname or IP address and port | The backend must have a network route to it. Open WebUI supports setting the endpoint through OLLAMA_BASE_URL or its connection settings. |
Open WebUI’s troubleshooting guidance explains why container networking matters: inside a container, localhost generally points back to that container. Depending on the deployment, a Docker service name, host.docker.internal, or an internal IP may be appropriate. Do not copy host-networking or port-mapping examples without checking the instructions for your operating system and setup.
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Connect Ollama in Open WebUI
- Start Ollama and make a model available. You can manage an Ollama instance and models through Open WebUI’s administration settings, or prepare the model through your existing Ollama setup.
- Open the administrator connection settings. In Open WebUI, go to Settings > Admin > Connections, then find the Ollama API connection. The interface can change between releases, so consult the documentation for your installed version if the labels differ.
- Enter the backend-reachable endpoint. For Docker Open WebUI connecting to Ollama on the host, the documented example is
http://host.docker.internal:11434. For other arrangements, enter the address appropriate to the network layout in the table above. For remote Ollama, you can also configureOLLAMA_BASE_URL. - Save or manage the connection and check model availability. The model selector should show models provided by that Ollama instance. If a needed model is not available, use the available model-management or pull flow.
- Start a new chat and select the model. Send a simple prompt to confirm that the selected model responds through the connection. This is a check for your own deployment, not a guarantee that every network or model configuration is working.
If Open WebUI cannot find models
- No models appear: Check the endpoint and confirm it is reachable from the Open WebUI backend. A URL that works from the host shell may fail from a container because it has a different network namespace.
- Docker Open WebUI cannot reach host Ollama: Try the documented
host.docker.internalexample where supported, or use an address suited to your platform and Docker configuration. - Ollama is on another machine: Check that the configured hostname or IP and port are reachable from the backend, and that the server is listening in a way that permits the intended connection. Use the official troubleshooting documentation for deployment-specific network guidance.
- The connection works but a model is missing: Confirm that the model is available from the connected Ollama instance, then use Open WebUI’s model-management options or pull flow as needed.
- Changing network settings seems to fix access: Limit exposure to the network access your deployment requires. Broadly binding a service can make it reachable by more devices than intended; reachability is not the same as safe access.
What “private” means with local Ollama
Ollama’s official FAQ says, “Ollama runs locally. We don’t see your prompts or data when you run locally.” That statement is specifically about running Ollama locally. Ollama’s FAQ also distinguishes cloud-hosted models and describes a configuration option for disabling Ollama Cloud features. When using a cloud-hosted model, do not assume the local-processing statement applies: the model is processed by the cloud service.
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- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
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- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
A local Ollama model does not, by itself, establish that every component of an Open WebUI deployment is private. The connection instructions do not make a blanket claim about extensions, remote endpoints, reverse proxies, telemetry, or other services you may enable. Review those services’ data handling and restrict network access to the people and systems that need it.
Keep Open WebUI data when replacing its Docker container
If you run Open WebUI in Docker, retain its persistent data mount when replacing or recreating the container. Open WebUI’s Docker quick-start examples mount a volume at /app/backend/data. Without keeping the configured persistent volume, data stored in the container may not carry over when the container is replaced.
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Check documentation against your installed release
The Open WebUI and Ollama setup pages are rolling documentation, and the cited instructions do not specify a single product version or geographic availability. If a menu label or deployment example differs from your installation, use the current documentation for that release and verify the endpoint from the backend’s point of view.
Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsSpecial offer. See more information about Outbyte and uninstall instructions. Please review EULA and Privacy policy.
Quick Recap
Bestseller No. 1
Bestseller No. 4
Rank #4
GMKtec AI Mini PC Ryzen Al Max+ 395 (up to 5.1GHz)
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
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GEEKOM A7 Mini PC,Ryzen 7 7730U(Low Power) 32GB RAM &500GB SSD(Expandable)
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