Hi @cbossi , You are right!

A 30-minute idle period precedes the endpoint's scaling down. You are billed for the compute resources used during this period, plus the actual serving time when requests are made. This is the current expected behaviour. You cannot currently reduce the idle timeout to less than 30 minutes.

If your use case does not require real-time request prediction, it is better to use a batch prediction by accumulating requests throughout the day and running them all at once. Alternatively, you can explore Azure Functions to host the model.