> For the complete documentation index, see [llms.txt](https://anyint.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://anyint.gitbook.io/docs/features/prompt-caching.md).

# prompt caching

Prompt caching reduces repeated-context cost and latency when the same prompt segments are reused. In practice, the main work is prompt design: stable prefixes are easier to reuse than constantly changing prompts.

## Good use cases

* stable system prompts
* repeated long documents
* reusable instruction blocks
* shared prompt templates across a team

## Practical guidance

* keep reusable context stable
* separate static instructions from user-specific content
* place large shared context before volatile user input
* monitor actual usage data instead of assuming a fixed discount across all models

## A good prompt layout

1. static policy and instructions
2. reusable long-form reference material
3. tool definitions or schema instructions
4. request-specific user content

## What breaks reuse

* injecting timestamps or random values into the static prefix
* rebuilding prompts in a slightly different order on every request
* mixing cached and non-cached content into one unstable blob

Caching behavior and savings can vary by model family, account setup, and plan. Check your actual usage metrics when you optimize for cost.