Prompt Caching Explained: What It Is and How It Works

By the TechScalpel team · Published November 4, 2026

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Every time you call an AI model, it reads your whole prompt again. If most of that prompt never changes, such as long instructions or a big document, you pay to process the same text again and again. Prompt caching fixes this.

How it works

The provider remembers how it processed the beginning of your prompt. On the next request with the same beginning, it reuses that work. Cached input is usually billed at a lower rate and returns faster.

The golden rule: static first, changing last

Caching only works when the start of the prompt is identical. Put things that never change (instructions, examples, documents, tool definitions) at the top, and the part that changes (the user question) at the end. A timestamp or user name placed at the very top breaks the cache every time.

Where it helps most

• Chatbots with a long system prompt
• Questions about the same long document
• Agents that send many tool definitions

Things to check with your provider

• Minimum prompt length for caching
• How long a cache lives (often minutes)
• Whether you must mark cacheable sections yourself
• The discount on cached tokens

Not the same as semantic caching

Semantic caching stores whole answers and reuses them for similar questions. It can save more, but may return a slightly outdated or mismatched answer. Prompt caching is safer because the model still answers fresh each time.

Rules and prices differ by provider and change often. Read the official documentation before you build.