Issue 33, Nov 5, 2026
The KV Cache Memory Trap
Senior ML Engineer interview at Google, and the interviewer asks:
“With a KV cache, each decode step only computes Q, K, V for the newest token. So it’s a free speedup, right? What did you actually trade away?”
Don’t say: “KV cache stores past keys and values so we don’t recompute them. Generation gets faster.”
Why saving FLOPs quietly starves your batch size and how memory bandwidth, not compute, actually caps your long-context inference throughput.
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The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.