Notice: Each tenant can only have a maximum of 10 containers. If you have reached this limit, please delete unused container to create a new one.
Step 1: In the AI Factory Portal, navigate to “GPU Container". From the list view, click button “Create New Container”

Step 2: Give your container a name

Step 3: Select GPU Instance
Currently, GPU Container only support card NVIDIA H100.

Step 4: Choose Template
We highly recommend our customers use built-in templates for faster deployment. Currently, GPU Container provides 5 templates: Ollama, Ollama WebUI, vLLM, Code Server, Jupyter Notebook.
- Built-in templates: user clicks on the dropdown icon at the end of template card.
- Custom template: in case users want to use their own image or use another image version, they can use feature “Custom Template”
- Click button “Custom Template”, a modal will be opened for user to input the new image information
- Click button “Save Changes” to save new image information
Step 5 (Optional): Configure the Advance Settings based on demands.
This section includes:
- HTTP Port: this information is required
- Persistent Disk: specify the amount of storage that users need to store training weights, models, etc.
- Environment Variables: key-value pairs injected into the container at runtime.
- Startup Command: command and arguments to run at the start of container.
Step 6: Click “Create New Container” to create.

Step 7: In case your balance is insufficient to create a new container, please navigate to Billing to add more credit, details instruction can be find here