# Context caching ### What is context caching ? Context caching is the ability to cache the KV (key-value) computations of the same context between requests. This feature helps speed up inference time by over 10 times when the request has the same context. The speedup is about 2 times when benchmarked with evaluation datasets like M3Exam. ### How does context caching is work ? Context caching is automatically triggered when requests have the same context within the same batch size. For example, if the endpoint has a batch size of 8 and each request has 1,024 tokens, and the requests share the same context for 900 tokens. Instead of the system calculating 1,024 \* 8 = 8,192 tokens. The system will calculate ((1,024 - 900) \* 8) + 1,024 = 2,016 tokens. This significantly reduces the compute required and improves the endpoint's latency. ### Use case * RAG * Few-shot prompting * Code Co-pilot --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.float16.cloud/getting-started/one-click-deploy/features/context-caching.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.