Prompt order can cut LLM costs through caching
can lower costs when the same opening part of a prompt is reused. Big often mention this across pricing pages, , or API notes, but the cost impact is not always easy to understand. Two prompts with nearly the same content can cost different amounts if their parts are arranged differently.
Putting the user question, variables, timestamps, metadata, or other request-specific details near the start can break the that the cache depends on. The practical rule is to put repeatable content first. s, fixed rules, examples, schemas, and output format should come before dynamic user input and request-specific data.
For products that call LLMs many times, this small prompt design choice can meaningfully affect and return on investment.
Key points
- can reduce cost when the same prompt prefix is reused.
- Putting changing details early can weaken or remove the cache benefit.
- Stable instructions, rules, examples, schemas, and formats should go first.
- User input and request-specific data should usually go near the end.
- For high-volume AI agents, prompt structure can directly affect .