Cut your LLM bill by 30 to 70%: the levers that work

Short summary

An AI production consultant shares practical levers for cutting LLM bills by 30-70% without degrading quality. The main issues are useless context sent on every call and defaulting to the most expensive model. Key tactics include caching identical inputs, routing simple tasks to cheaper models, trimming dead context, batching bulk processing, and favoring short targeted instructions over long directives.

• •Cache near-duplicate calls to eliminate redundant token spend
• •Route each request to the cheapest capable model instead of defaulting to premium
• •Trim dead context and batch bulk processing for 30-70% bill reduction at equal quality

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