Reducing LLM Costs Without Sacrificing Quality

When you move from prototype to production, LLM API costs have a way of surprising even well-prepared teams. A system that costs pennies per request in testing can generate thousands in monthly bills at scale.

Prompt engineering for efficiency

The simplest lever is prompt optimisation. Shorter, more focused prompts reduce token consumption without degrading quality. Structured output formats (JSON mode, function calling) eliminate the need for post-processing that often requires additional LLM calls.

Model routing and cascading

Not every request needs your most powerful (and expensive) model. A routing layer that directs simple queries to smaller, cheaper models and reserves premium models for complex tasks can cut costs dramatically while maintaining quality where it matters.