Deploy
Deploy a Trained Model
Go from a completed training run to a live endpoint in a few clicks.
When training completes, the model is automatically registered and ready to deploy. No manual promotion step.
Deployments are created within a project, and access is scoped to that project — sibling projects in the same team cannot call them. When you create a deployment, you give it a name — the model path becomes your team/org slug followed by that name (e.g. acme-corp/my-model).
Starting a deployment
There are a few ways to get started:
- From the Dedicated page — click Create Deployment
- From a completed training run — click deploy directly from the training detail page
- From the Models page — open the model's detail page and click deploy
All three paths lead to the same flow.
The flow
Name the deployment
Give it a descriptive name. This becomes the second part of your model path (e.g. acme-corp/my-model).
Deploy
Select your instance type and count, then click deploy.
Wait for warm-up
The deployment takes a few minutes to 20–30 minutes to come online. This time is spent allocating compute and spinning up the GPU.
After deployment
Once the endpoint is live, you can call it using the same OpenAI-compatible API you're already using. Just swap in your model path.