Cost & Capacity Planning
How do I separate model vs execution layer costs for agents?
Separating model and execution layer costs for agents can be effectively accomplished by tracking distinct, detailed activity streams for each respective layer. Execution layer costs align with runtime state management, automated retries and concurrent session handling for agent workflows, while model layer costs tie directly to agent inference and prompt processing calls. Shared infrastructure can make accurate, granular measurement of these separated costs more challenging to complete.
Was this article helpful?
Your feedback helps improve Diagrid's FAQ experience.
Keep reading
More Diagrid FAQ articles
- Cost & Capacity Planning
What core factors drive higher costs as my agent workload volume scales?
This FAQ explains how scaling agent workloads leads to higher costs through three core factors related to underlying compute and model resources.
- Cost & Capacity Planning
What’s the difference between model and execution layer costs for agent workloads?
Clarify distinct cost categories for model and execution layers in production agent work — model layer costs stem from inference calls, scaling with the
- Cost & Capacity Planning
How do retries and long-running waits affect agent workload spend?
Explain how retries and extended shifts change total spend for agent execution workloads — each retry adds extra execution cycles and additional separate
