How to Allocate OpenRouter Costs by Customer, Agent, or Workload

OpenRouter’s unified access to multiple AI providers can make overall spending easy to see but difficult to attribute to specific customers, products, agents, features, or workloads. The post recommends attaching application-known metadata through the `trace` field, including identifiers such as customer, agent, environment, feature, and invocation, then aggregating actual per-request cost and token data returned in usage information. It distinguishes `session_id`, which groups related conversations or agent runs and can affect sticky provider routing and cache use, from `trace`, which is intended for flexible cost-allocation tags. For multi-step agent workflows, grouping all model calls under an invocation ID produces more useful unit-cost measures than examining individual requests alone. When categories are not known in advance, OpenRouter’s beta Classifiers can asynchronously infer labels such as task type and complexity, though classification adds token costs. These capabilities can support AI unit-economics analysis, helping teams connect inference spend with revenue, margins, feature costs, and model-optimization opportunities; Vantage is presented as a platform that integrates OpenRouter cost data with broader cloud and business reporting.

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