Compare static, dynamic, and continuous batching for LLM serving and state the tradeoffs.
Three batching strategies, three very different latency profiles. Choosing wrong leaves throughput or tail latency on the floor. Here is what each one costs and when to use it.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Three batching strategies, three very different latency profiles. Choosing wrong leaves throughput or tail latency on the floor. Here is what each one costs and when to use it.
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.
