Quickstart
Install GPUStack
If you are using NVIDIA GPUs, ensure Docker and NVIDIA Container Toolkit are installed on your system. Then, run the following command to start the GPUStack server.
docker run -d --name gpustack \
--restart=unless-stopped \
--gpus all \
--network=host \
--ipc=host \
-v gpustack-data:/var/lib/gpustack \
gpustack/gpustack
For more details on the installation or other GPU hardware platforms, please refer to the Installation Documentation.
After the server starts, run the following command to get the default admin password:
docker exec gpustack cat /var/lib/gpustack/initial_admin_password
Open your browser and navigate to http://your_host_ip
to access the GPUStack UI. Use the default username admin
and the password you retrieved above to log in.
Download the installer and run it to install GPUStack.
Note
Supported platforms: Apple Silicon (M series), macOS 14 or later
After the installation is complete, the GPUStack icon will appear in the status bar. Click the GPUStack icon in the status bar and select Web Console
to open the GPUStack UI in your browser.
Download the installer and run it to install GPUStack.
Note
Supported platforms: Windows 10 and Windows 11
After the installation is complete, the GPUStack icon will appear in the system tray. Click the GPUStack icon in the system tray and select Web Console
to open the GPUStack UI in your browser.
Deploy a Model
-
Navigate to the
Catalog
page in the GPUStack UI. -
Select the
Qwen3
model from the list of available models. -
After the deployment compatibility checks pass, click the
Save
button to deploy the model.
- GPUStack will start downloading the model files and deploying the model. When the deployment status shows
Running
, the model has been deployed successfully.
- Click
Playground - Chat
in the navigation menu, check that the modelqwen3
is selected from the top-rightModel
dropdown. Now you can chat with the model in the UI playground.
Use the model via API
-
Hover over the user avatar and navigate to the
API Keys
page, then click theNew API Key
button. -
Fill in the
Name
and click theSave
button. -
Copy the generated API key and save it somewhere safe. Please note that you can only see it once on creation.
-
You can now use the API key to access the OpenAI-compatible API endpoints provided by GPUStack. For example, use curl as the following:
# Replace `your_api_key` and `your_gpustack_server_url`
# with your actual API key and GPUStack server URL.
export GPUSTACK_API_KEY=your_api_key
curl http://your_gpustack_server_url/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $GPUSTACK_API_KEY" \
-d '{
"model": "qwen3",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Tell me a joke."
}
],
"stream": true
}'
Cleanup
After you complete using the deployed model, you can go to the Deployments
page in the GPUStack UI and delete the model to free up resources.