Control LLM costs with context caching
Introduction Some large language models (LLMs), such as Gemini 1.5 Flash or Gemini 1.5 Pro, have a very large context window. This is very useful if you want to analyze a big chunk of data, such as a whole book or a long video. On the other hand, it can get quite expensive if you keep sending the same large data in your prompts. Context caching can help.
Context caching is useful in reducing costs when a substantial context is referenced repeatedly by shorter requests such as:
Read More →