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Why does naive Kubernetes GPU scheduling strand GPUs, and how would you serve thousands of models cheaply?

The cluster shows eight free GPUs and your four-GPU pod still won't schedule, the fragmentation puzzle GPU-platform rounds open with. Bin-packing vs. spreading, MIG/MPS/time-slicing for the small-model problem, and the pod-per-model math that breaks at scale.

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