Deployment & Scaling · Advanced
Cost and Scale: Pricing, Context Caching, Batch and Provisioned Throughput
What actually bills on Google Cloud AI, the idle resources that quietly drain budgets, and the four levers — model tier, caching, batch, provisioned throughput — that change the economics.
- 1.3 hours lesson
- advanced level
- Google Cloud AI Track
- Narrated presentation
What you’ll learn
- Per-token input and output pricing, with output typically several times input
- Multimodal and long-context inputs as priced decisions
- Machine-hour resources: endpoints, Vector Search index endpoints, notebooks, GPU pools
- Model-tier routing as the largest single cost lever
- Implicit and explicit context caching for shared prefixes
- Batch prediction pricing for non-synchronous work
- Provisioned Throughput for sustained, predictable volume only
- Labels, billing export to BigQuery and per-feature cost dashboards
Inside this lesson
A narrated, slide-by-slide presentation with 1 prediction exercise, 1 knowledge check, 2 videos. You answer as you go, and the platform checks your work.