The speed of chip iteration is astonishingly fast. A batch of solid-performing processors are directly eliminated because they do not meet the "flagship" standard. This kind of waste is truly lamentable. One idea worth pondering is: instead of letting these "quasi-first-class" hardware accumulate as waste, why not reassemble them into a network through clever algorithm design? The charm of distributed computing lies exactly here—hundreds of mid-to-high-end GPUs working together, with proper task scheduling and load balancing, can fully handle inference tasks that originally required a single top-tier acceleration card. This not only activates dormant hardware capacity but also stimulates technological imagination.