Agent loops (particularly coding agents) have a huge amount of repetition, because the entire context is included in every model request. So long as it's at the start of the input and doesn't change, it will be able to hit the KV cache (assuming the model provider actually has the prefix in cache).

This only works because prompt caching is done by matching prefixes, not the entire input.

Their blob explains it best, although this is a link to an older version design: https://github.com/esengine/DeepSeek-Reasonix/blob/v1/docs/A...

From my understanding if previous tokens are frozen and guaranteed to be immutable you can leverage that.

It probably depends on what you're doing, but imagine you're something in the shape of a search engine. How many user queries are unique vs. the same thing someone else searched for an hour ago?

In a typical agent loop your N-th LLM request naturally becomes prefix for the (N+1)-th request. As the thread grows longer, cache hit rate converges to 100% and unit pricing for cached tokens is 10-100x cheaper.