A Practical Playbook for Reducing LLM Spend

Cost work is most effective when it is trace-led. Start by understanding where spend comes from, then decide which fixes will reduce waste without weakening the workflow.

The fastest wins often come from removing unnecessary context, tightening retrieval, and routing lower-complexity tasks away from premium models when the quality bar allows it.

Prompt compression

Trim repetitive instructions, cut irrelevant examples, and send only the context the task needs. Shorter prompts usually improve both cost and latency.

Model routing

Not every step needs the same model. Classification, formatting, and routing tasks often work well on smaller models, while higher-complexity reasoning stays on a stronger model.

Semantic caching

Repeated or near-duplicate requests can often be served from a cache if freshness rules are clear. This is especially useful in internal help, summarization, and support workflows.

Validate before rollout

Every cost change should be checked against representative tasks. If quality, safety, or escalation volume worsens, the savings may not be worth it.