As open-weight models close the capability gap, the conversation shifts from “Which model is smartest?” to: → What does inference actually cost at scale? → When should workloads be dynamically routed? → How important will sovereign AI infrastructure become? For AI builders and leaders, architecture + economics + deployment strategy are becoming as important as model choice. The frontier is no longer just the model. It is the system around it. What do you think will matter most: model capability, cost, or sovereignty?