Prompt caching is a technique to reduce costs and latency in LLM applications by reusing computed prompt states. It involves splitting prompts into a stable prefix (system prompt, tool definitions) and a volatile suffix (user query). The first call incurs a higher cost for prefilling the prefix, but subsequent calls with identical prefixes can load the cached state, reducing the cost of those tokens by approximately 90% and significantly decreasing latency. This method requires deterministic prefixes, as any change invalidates the cache, leading to higher bills without explicit errors. AI
IMPACT Reduces operational costs and improves response times for LLM applications by optimizing prompt processing.
RANK_REASON The item describes a technical optimization for LLM applications, not a new model release or core research.
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