Optimizing cost and latency with Amazon Bedrock prompt caching
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Prompt caching in Amazon Bedrock can cut input token costs by up to 90% when you repeatedly send the same context to foundation models. This post walks through six practical prompt caching scenarios using the Converse API: message content, system prompt, tool definition, mixed TTL, tenant isolation, and LangChain integration.
Prompt caching in Amazon Bedrock can reduce your input token costs by up to 90 percent when you repeatedly send the same context to foundation models, based on Amazon Bedrock prompt caching pricing . Without caching, a 10,000-token contract sent alongside 50 user questions means 500,000 input tokens billed at full price for content the model has already processed. You can mitigate this issue by shortening prompts, reducing context windows, or implementing application-level caching. Each option…
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