AlternativePhusion

Cut Your LLM Bill 80%

Prompt caching and token economics

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Where LLM spend goes and the levers that cut it: prompt caching, model tiering, context trimming, output caps and batching. Instant PDF download.

What you get

  • You get a PDF guide with the math for each lever.

Description

A guide to cutting what you spend on language model calls without lowering the quality of the answers.

It starts with where the money goes: input tokens and output tokens. Then it works through the levers one at a time: prompt caching, model tiering, context trimming and output caps.

It also covers batch requests and response caching, and why you measure first.

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