Semantic Caching for Production LLM Systems: Thresholds, Layers, and Failure Modes
Frontier large language models cost between $0.15 and $15 per million tokens depending on model class. Semantic caching can remove the majority of these calls from the critical path when production workloads repeat similar queries. Yet despite five years of tooling (GPTCache, SemCache, Redis Vector Similarity, Weaviate, Pinecone), most engineering teams never deploy it. The barrier is not the availability of vector databases. It is that semantic caching moves the failure mode from "slow" to "sub
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