Start with an outcome someone can accept
A useful economic comparison begins with a task definition. An equipment review, document extraction, or proposed maintenance action needs an identifiable input and an accepted result. Write down who verifies that result, which evidence they need, and what makes it usable. Include the required accuracy, response time, permissions, and recovery behavior. A fluent answer may still leave the operating task unfinished. The worksheet should therefore describe the business outcome in language that its accountable reviewer can assess consistently across every architecture being compared.
Draw the cost boundary before collecting totals
Create a cost register for the agreed evaluation period. Record model execution, retrieval, storage, supporting services, and the human review needed to accept or correct results. Include failed attempts, retries, and recovery work within that same boundary. For dedicated infrastructure, state how reserved capacity, operating hours, and shared costs are allocated. Keep one-time implementation costs visible in a separate line so the comparison can show operating economics and the investment decision. Record estimates as estimates, with their source and the assumption that would change them.
Count verified outcomes once
Calculate cost per verified task as total in-scope workload cost divided by the number of distinct task outcomes that satisfy the agreed acceptance criteria. Give each task a stable identity so several retries cannot become several successful outcomes. Retain the rejected and unresolved cases alongside the accepted count. If no task qualifies, report the absence of accepted outcomes and leave the ratio undefined. A denominator that silently excludes difficult work can make an architecture appear economical while concealing the effort required to complete the actual workload.
Build a worksheet that preserves the comparison
Use one row per task, with fields for task identity, input revision, task category, configuration, attempts, elapsed time, measured resource use, review effort, and final disposition. Add the acceptance evidence and reviewer to the row. Maintain a second sheet for shared costs and allocation rules, then reconcile its total with the task register. Record the measurement window, currency, and data gaps. This structure gives an engineering reviewer a way to trace a surprising total back to the work and gives a finance reviewer an explicit basis for the allocation.
Compare architectures against the same requirements
Keep the input mix, quality threshold, verification method, and operating constraints consistent. Include representative difficult cases and an evaluation set reserved from configuration selection. Report latency and recovery results beside the cost ratio; a lower cost cannot establish suitability when the required service condition is missed. Where traffic or infrastructure utilization differs, explain the difference and show its effect separately. Sensitivity analysis can explore uncertain prices or volumes, but the resulting scenarios should remain distinguishable from observations made during the evaluation.
Finish with a bounded decision
The decision record should identify the preferred option, the evidence supporting it, the unresolved assumptions, and the conditions that would trigger another review. Agree the owner of the next measurement and the scope of any deployment change. AssetSolve AI Inference Economics organizes this discussion around task quality, context and state, resource sizing, and acceptance evidence. A useful first scope is one material workload with an agreed baseline. Its output is a reviewable infrastructure or runtime decision; any claim of realized savings needs subsequent operating evidence.