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Language & LLMs

Prompt Caching

Reusing the computation for a prompt prefix you've sent before — the largest cost saving available to most applications, and most of them don't use it.

Reading level: Curious
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When not to use it

  • With short prompts. Below the provider's minimum it doesn't cache at all.
  • With anything variable at the top. A timestamp in your system prompt disables it for the whole application, silently.
  • With sparse traffic. A five-minute TTL and a request every ten minutes never hits.
  • Where a cache write costs a premium and you won't hit. You've made it more expensive.

Reach for something else instead

  • Reordering your prompt — this is the fix, not an alternative. Stable first, variable last.
  • A shorter prompt — if it won't cache, it should be small.
  • Fine-tuning — bake the instructions into the weights instead of sending them.
  • Batching — different lever, also worth pulling.

Sources & further reading

  • Anthropic, Prompt caching documentation — the primary source for the constraints; read the provider's, not the coverage.
  • Gim et al. (2023), Prompt Cache: Modular Attention Reuse for Low-Latency Inference — the research attempt at escaping the prefix constraint.
  • Kwon et al. (2023), Efficient Memory Management for Large Language Model Serving with PagedAttention — vLLM; the KV-cache management this rests on.

Primary sources, listed so you can check the claims on this page rather than take them on trust.

Where people go wrong

  • Putting the user's question first. Nothing after it caches, ever.
  • A timestamp or session ID near the top. Silently disables everything, and the bill never explains itself.
  • Not checking cache-hit metrics. Every provider reports them; almost nobody looks.
  • Keeping prompts short out of habit. If the prefix is cached, long is nearly free.

At a glance

FieldLanguage & LLMs
What it cachesthe KV state of a prompt prefix
Savingup to ~90% on the cached portion
The one rulestable content first, variable content last
Why prefix-onlyevery token's state depends on all prior tokens; that's causal attention
Typical TTL~5 minutes
DifficultyBeginner
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Often compared with

Prompt caching vs. shortening your prompt — one makes a long prefix nearly free, the other throws it away. If your prompt is stable, the first is strictly better.