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Amazon Bedrock Prompt Caching Guide for OpenAI Models

1 reports1 sources10/26/2026 updated

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AWS Blog released a guide on using prompt caching with OpenAI models on Amazon Bedrock. Users must ensure reusable prefixes reach 1,024 tokens to qualify and use explicit mode with a 30-minute TTL, identifying shareable requests via prompt_cache_key. The mechanism aims to allow AI agents to avoid re-reading full context on each startup, significantly reducing costs and improving response consistency.

Written with AI from the reporting · updated 10/26/2026

Latest developmentOct 27, 01:27
Prompt caching reduces costs for AI agents on Amazon Bedrock
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  1. 1Unclassified fact stationOct 27, 00:00recorded Oct 27, 02:23single source

    Prompt caching patterns for using OpenAI models on Amazon Be

    Read original source ↗ AWS Machine Learning BlogReplay this moment in the explorer
    Evidence & revisions · 1 source records
    Subject：
    Claudio Mazzoni
    Action：
    发布指南文章
    Object：
    AI agent prompt caching 机制
    Occurred (fact side)：
    Oct 27, 00:00
    AWS Machine Learning Blog ↗Report pageOriginal / first version
    Published (valid side)：
    Oct 27, 01:27
    First seen (known side)：
    Oct 27, 02:23
    Fact stationSingle source · one-sided claim

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Oct 27
  1. AWS Machine Learning BlogFirst-party sourceRelated fact: single source
    Prompt caching reduces costs for AI agents on Amazon Bedrock

    Report first recorded Oct 27, 02:23

    Amazon Bedrock introduces prompt caching to lower costs for AI agents. The service stores the input prompt, including tools and instructions, and reuses the processed state on subsequent requests. This avoids re-processing the entire context, reducing input token prices. Caching can be implicit, where Bedrock automatically identifies reusable prefixes, or explicit, where developers specify the cache key. The feature is particularly beneficial for multi-turn conversations and agents that spawn helpers, as it maintains consistency while cutting expenses.

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