Running trained models on hardware they were not designed for — phones, embedded boards, sensor nodes, microcontrollers — where memory, power and thermal budgets are fixed before the model is chosen and there is no scaling out. The machine is also in someone else's hands: often offline, thermally throttled, or several versions behind, and never redeployable on demand.