Build a predictable per-request pricing model for AI services

A practical framework to map model cost, latency and support overhead into a pricing layer your customers understand.

Usage-based AI pricing only works when every request is mapped to a real operational cost. That means tracking model provider cost, average latency, retry rate, moderation overhead and support exposure before publishing a public price table.

A healthy pricing model separates low-cost interactions from premium workflows. Lightweight chat, heavy image generation and long-form video should not share the same credit weight or package economics.

For global SaaS products, pricing communication also needs to be transparent across languages and markets. Explain how credits behave, when refunds happen, what counts as a failed request and how peak load can affect consumption.