Optimization guide
How to Reduce AI API Cost
Most AI cost reductions come from sending less repeated context and generating only the answer length the user actually needs.
Trim input context
Input tokens grow quietly. Old chat history, repeated system instructions, irrelevant retrieved chunks, copied examples, and full documents can travel with every request. Start by removing anything that does not change the answer.
For document workflows, retrieve fewer but better passages. For coding workflows, send only the files involved in the current task. For reporting workflows, summarize raw notes first and reuse the summary instead of re-sending the original material each day.
Control output length
Output tokens are often more expensive than input tokens, so answer format matters. Ask for concise bullets, fixed sections, JSON schemas, or a specific word limit. Avoid asking for both a long explanation and a full table unless the user needs both.
Example
If a report workflow generates 10,000 output tokens per run, reducing the answer by 40% saves 4,000 output tokens every run. At 30 runs per day, that is 120,000 fewer output tokens per day before model-specific pricing.
Cache and batch repeated work
Do not repeat expensive work when the underlying material has not changed. Store document summaries, repository maps, extracted entities, and previous classifications. Batch similar tasks when possible, especially for offline processing that does not need an immediate answer.
Route by difficulty
Not every task needs the strongest model. Use lower-cost models for routing, classification, extraction, rewriting, and first drafts. Use stronger models for final review, complex reasoning, sensitive decisions, or tasks where mistakes are expensive.
Measure real usage
After launch, compare calculator estimates with actual API usage fields. Track input tokens, output tokens, retries, failed calls, average answer length, and cost per successful user action. Optimization is easier when the team can see which workflow creates the most spend.