@h100envy: Ex-vLLM core contributor explained how to make LLM inference 10x cheaper in 34 minutes - better than $3000 inference op…
Summary
An ex-vLLM core contributor explains how to reduce LLM inference cost by 10x using LMCache with KV cache offloading to CPU/SSD/remote storage, a technique used by production stacks like Bloomberg.
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Ex-vLLM core contributor explained how to make LLM inference 10x cheaper in 34 minutes - better than $3000 inference optimization bootcamps.
request comes in -> check LMCache -> hit? load KV cache from CPU/SSD/remote -> skip prefill -> serve.
That loop is why Bloomberg and other production stacks now push 300 terabytes of KV cache per week.
LMCache + vLLM + CPU/SSD/remote storage + zero-copy CUDA kernels - that’s the stack.
Watch and save it, then wire the KV-offload into your inference stack.
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