Cutting LLM Costs Without Cutting Quality
Caching, routing, and right-sizing models to keep an AI feature's bill sane at scale.
LLM features are easy to ship and easy to overspend on. A few patterns keep the bill proportional to the value.
Cache aggressively
Many prompts repeat. Caching identical and semantically similar requests can cut spend dramatically with zero quality loss.
Route to the right model
Not every request needs your most expensive model. Route simple tasks to smaller, cheaper models and reserve the big one for genuinely hard queries.
Spend tokens wisely
Tighter prompts, trimmed context, and structured outputs all reduce token count. Measure cost per request and treat it as a budget, not an afterthought.
