Cost & Capacity Planning
What core factors raise costs as my agent workload volume scales?
The core factors driving cost increases as your agent workload scales fall into three key operational and workflow categories. These include per-agent execution cycles including retries and long-running waits that add load, model inference calls tied to your agent tasks that generate separate spend, and operational overhead that scales with total number of concurrent active sessions. Cost attribution can be blurred when model and execution layers share underlying infrastructure resources.
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
