KV Cache Offloading: Free GPU Memory in Long-Context LLM Serving
A practical framework for deciding when to offload KV cache
LLM inference workloads diverge in concurrent users, context length, and traffic patterns, each shifting where KV cache pressure lands on GPU memory. This guide maps workloads to the right offloading verdict, weighs the three cost variables that decide it, and pinpoints where offloading would actually regress performance.
Offloading doesn’t work for every workload
Offloading does not always improve performance — depending on workload conditions, it can add latency or reduce throughput. Whether gains or regressions appear depends on a handful of environmental factors that you can only judge after checking them. Use this guide to walk through the workload-effect matrix and the decision criteria.
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