RunPod: GPU compute, two products, one bill

RunPod sells GPU time two ways and they bill on opposite philosophies. Get the choice wrong and you either pay a steep premium for idle work or you pay 24/7 for a box that sits warm doing nothing. Everything below is the RunPod-specific operational playbook: which product a workload belongs on, how to write a worker that does not waste cold-start seconds, and which knobs actually move the number on the invoice.

The two products:

• Pods — rent a GPU container by the hour. It runs continuously while it is up, billed every hour whether busy or idle. Your dev box, your training job, your Jupyter.
• Serverless — per-second autoscaling workers. Billed only while a worker is actually running a job, from worker start to full stop, rounded up to the second. Costs roughly 2-3x the equivalent hourly pod rate, but idle gaps cost nothing on flex workers.

RunPod charges zero egress/ingress fees — bandwidth in and out is free, unlike the hyperscalers. That removes one variable from cost math: you only reason about GPU-seconds and storage.