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OpenAI Prompt Caching

Free

Prompt prefix

FreeFree tier
Inputs: textOutputs: text
Type
Open Source
Founded
2015
Company
OpenAI
Visit Website GitHub (38 stars)
LinksXLinkedIn

About OpenAI Prompt Caching

OpenAI Prompt Caching is a feature of the OpenAI API that automatically caches the computational work associated with repetitive prompt prefixes. When the same prompt prefix (e.g., a system message, few-shot examples, or a long instruction) is reused across multiple API calls, the cached result is served, reducing latency and lowering costs. This feature integrates seamlessly into existing API workflows without requiring any manual configuration or changes to the code—the caching is applied automatically for supported models. Prompt caching is especially beneficial for applications that send consistent instructions or context in every request, such as chatbot system prompts, document analysis pipelines, or multi-turn conversations with a fixed preamble.

Key Features

Automatically caches prompt prefixes for repeated API requests
Reduces latency for cached prompts
Lowers API costs for repetitive content
No manual configuration or code changes required
Seamless integration with existing OpenAI API calls
Supports a variety of models (GPT-4o, etc.)

Pros & Cons

Pros
  • Significant cost savings for applications with repeated prompt prefixes
  • Lower latency for cached requests improves user experience
  • Automatic activation with no extra code or configuration
  • Transparent to the developer—caching happens behind the scenes
Cons
  • Only beneficial when prompt prefixes are repeated; unique prompts see no cache benefit
  • Limited to prefix caching; mid-prompt or suffix caching is not supported
  • Cache misses can occur if prompts vary too much, reducing effectiveness
  • Not all OpenAI models support prompt caching; need to verify model compatibility

Best For

Reusing system prompts across many user interactionsCaching few-shot examples for consistent model behaviorRepeated data analysis or summarization with identical instructionsMulti-turn chatbots with a fixed context preambleBatch processing where each request shares a long prefix

FAQ

How does prompt caching work?
Prompt caching automatically detects when a prompt prefix (the beginning portion of a request) has been seen in a previous request. The computation for that prefix is cached, so subsequent requests with the same prefix can reuse the cached result, reducing latency and cost.
Which OpenAI models support prompt caching?
Prompt caching is supported on several models including GPT-4o, GPT-4o-mini, and others. The official OpenAI documentation lists supported models; check the Prompt Caching guide for the latest list.
Is prompt caching enabled by default?
Yes, prompt caching is automatically enabled for supported models in the API. Developers do not need to take any action to enable it.
Does prompt caching affect output quality?
No, prompt caching is a performance optimization that does not alter the model's output. The cached computation yields identical results to a non-cached request.