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This article emphasizes the importance of LLM caching in production systems to reduce latency, GPU utilization, and costs, and introduces LMCache, an open-source KV cache management layer for scalable LLM inference.
This paper proposes that the KV cache in transformers acts as a notebook of memoized conclusions, enabling surgical editing and composition without full recomputation. The method achieves significant latency reductions while preserving decision equivalence across model scales.