You have more models than GPUs. How do you share GPUs across many models and teams?
Pinning one GPU per model leaves most of a fleet stranded on idle silicon. Sharing safely is a genuine systems problem with four distinct mechanisms, each suited to a different traffic shape. Here is how to choose.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Pinning one GPU per model leaves most of a fleet stranded on idle silicon. Sharing safely is a genuine systems problem with four distinct mechanisms, each suited to a different traffic shape. Here is how to choose.
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.
