A critical test of open-source AI viability is currently unfolding. Nathan Lambert argues that the window for open models to remain competitive is closing rapidly. This pressure stems from the widening gap between proprietary systems and public weights. Researchers must now prove that open-source architectures can scale efficiently or risk becoming mere footnotes.