Your LLM decode is slow even though GPU compute utilization looks low. Why is it memory-bandwidth-bound?
The counterintuitive reality of LLM serving: token generation is capped by how quickly you can read weights out of memory, not by arithmetic. Once that clicks, the entire optimization menu follows from one number.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
The counterintuitive reality of LLM serving: token generation is capped by how quickly you can read weights out of memory, not by arithmetic. Once that clicks, the entire optimization menu follows from one number.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
