How does continuous (in-flight) batching improve LLM serving throughput vs static batching?
Continuous batching is the biggest single throughput lever in modern LLM serving. The signal is explaining why static batching leaves the GPU idle on variable-length generation, and why PagedAttention is what makes the fix practical.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Continuous batching is the biggest single throughput lever in modern LLM serving. The signal is explaining why static batching leaves the GPU idle on variable-length generation, and why PagedAttention is what makes the fix practical.
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.