Property Moderation Router: Compare 3 Startup API Token Costs with One Key

Short answer: for a property-management startup, the cheapest one-key router is the one that minimizes cost per correctly classified moderation report on your own replay set while preserving a provider-neutral request, response, and error contract. Raw token rates alone cannot make that choice. Choice Best fit Main catch Measure first Managed multi-provider router Small team optimizing time-to-first-call Another control plane owns the routing boundary Valid classifications per dollar Self-hosted gateway Team that needs policy and telemetry under its control You own upgrades, capacity, and incident response Operator hours plus inference cost Thin in-app adapters Narrow model set and strict contract control Every new capability adds adapter work Change lead time and test burden My default for an early startup app is a managed router behind a tiny internal interface, with request fixtures stored outside the router. Choose the self-hosted runner-up when data-path control or custom routing policy is more important than low configuration overhead. Choose direct adapters when the application genuinely uses only a small, stable slice of each provider API. This is a decision about portability, not a hunt for a permanent lowest price. OpenAI, Claude, and Gemini differ in message shapes, structured-output behavior, usage accounting, and model lifecycle. A shared API key removes credential sprawl; it doesn't erase those differences. How should a startup app compare token cost across one-key routers? Start with the unit of work: one moderation report reaching a human reviewer with a valid label, confidence, rationale, and trace ID. A property manager does not buy tokens for their own sake. They need reports such as harassment , fraud , safety , or noise triaged consistently enough that urgent cases rise and ambiguous cases stay in the human queue. The useful equation is: effective cost = inference charges + router charges + retries + invalid-output handling + operational labor T