
LLM Costs Soaring? Semantic Caching Slashes Bills by 73%
Semantic caching, which focuses on the meaning of queries rather than exact wording, can drastically reduce LLM API costs, as demonstrated by a 73% reduction in one case study. Traditional exact-match caching fails to capture the significant portion of user queries that are semantically similar but phrased differently, leading to unnecessary LLM processing and increased expenses; semantic caching addresses this by caching based on the meaning of the query. This approach highlights the importance of understanding AI concepts like semantic similarity for optimizing LLM applications and managing their associated costs.

















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