How do you serve multiple models on shared GPUs using MIG, MPS, or model swapping?
Most models do not fill a GPU, so one model per GPU wastes money. The three sharing mechanisms (MIG, MPS, swapping) differ widely in isolation and overhead. Here is how to pick.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Most models do not fill a GPU, so one model per GPU wastes money. The three sharing mechanisms (MIG, MPS, swapping) differ widely in isolation and overhead. Here is how to pick.
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.
