Most teams compare AI APIs by model quality first and price second. That is backwards once you have real usage. The line item that matters is usually not "price per token" by itself. It is: monthly cost = requests × (avg input tokens × input price per token) + (avg output tokens × output price per token) + retries - cache savings Enter fullscreen mode Exit fullscreen mode Here are the five numbers I check before choosing a model. 1. Input/output token ratio Input and output are priced differently on most APIs. For chatbots, support agents, code review tools, and report generators, output can dominate the bill because the model writes much more than the user sends. A cheap-input model can still be expensive if its output price is high and your responses are long. 2. Cache hit rate If your app repeatedly sends the same system prompt, tool schema, policies, or long context, cached input pricing can change the economics.…