Inference cost is a product decision

Inference cost is usually treated as an infrastructure line item, something to optimize after launch. But the choices that drive it, model size, latency targets, caching, decide both your gross margin and how the product feels to use. That makes them product decisions, and they belong in the design conversation, not the cleanup phase.

The levers that matter

• Right-size the model. The largest model is rarely the best fit; a smaller one tuned to the task is often faster, cheaper, and good enough.
• Cache aggressively. Repeated and near-repeated queries should never hit the model twice at full price.
• Set a latency budget. A response that costs less but arrives slower can still lose the user; balance the two on purpose.

Decide these early and economics and experience reinforce each other. Decide them late and you are refactoring under margin pressure.

We design AI features with the unit economics in view from day one. Explore our other insights or get in touch if you would like to talk it through.