FinOps Framework
FinOps Foundation — supporting context for cost, usage, allocation, and unit-economics practice.
Definition
Make the denominator explicit.
Expense per inference is a possible operating ratio that assigns a defined set of direct and shared expenses across a stated measure of inference activity. It is useful only when the expense scope, allocation policy, workload mix, failed work, and definition of an inference are all stated.
Why it matters
A ratio can clarify tradeoffs without pretending to settle them.
AI teams may need to compare cost-to-serve trends across models, workloads, environments, or time periods. A stated ratio can make the question discussable, while preserving the decisions required to choose an allocation method and denominator.
Evidence and terminology boundary
LJP descriptive vocabulary; supporting FinOps context.
“Expense per Inference” is an LJP descriptive identity, not an adopted FinOps metric or accounting standard. The FinOps Framework supports the broader practice of making technology-value decisions with accessible, timely, and accurate cost data, including unit economics. FOCUS is an open specification for normalizing technology billing datasets. Neither source establishes this exact term, a universal allocation methodology, or a required inference metric.
FOCUS Specification
FinOps Open Cost & Usage Specification — supporting context for normalized billing data, including AI.
Machine-readable resources
Public identity resources
Namespace manifest · LLM summary · Robots policy · Sitemap
No ontology is published: this page defines a bounded descriptive identity, not a reusable formal vocabulary.
Credibility boundary
What this page does not claim.
This identity provides public technical orientation and a stable descriptive reference. It does not by itself operate a service, control plane, runtime, database, agent, or standards authority.
It is not an accounting standard, universal cost-allocation methodology, pricing requirement, financial-reporting treatment, FinOps endorsement, or mandatory metric for every AI environment.
Library context
Portfolio discovery record
View the Library record. Licensing, stewardship, partnership or acquisition discussions welcome.