1월 6, 2026

✨ How to Reduce Cost and Latency of Your RAG Application Using Semantic LLM Caching

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Semantic caching in LLM (Large Language Model) applications optimizes performance by storing and reusing responses based on semantic similarity rather than exact text matches. When a new query arrives, it’s converted into an embedding and compared with cached ones using similarity search. If a close

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Semantic caching in LLM (Large Language Model) applications optimizes performance by storing and reusing responses based on semantic similarity rather than exact text matches. When a new query arrives, it’s converted into an embedding and compared with cached ones using similarity search. If a close match is found (above a similarity threshold), the cached response […]
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