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Why $/GPU-Hour Is the Wrong Number to Optimize

GPU hourly pricing is easy to compare and easy to get wrong. A framework for evaluating AI inference infrastructure on cost per unit of output instead.

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Outline

  • Why hourly GPU pricing became the default comparison
  • What it leaves out: utilization, batching, memory headroom, traffic shape
  • Defining the unit of output for your application
  • Building a cost-per-unit model that a CFO and a CTO both trust
  • What to measure before and after an infrastructure change

Next step

Want This Applied to Your Workload?

Frameworks are a starting point. A benchmark of your actual infrastructure is the answer.