Grad students love open Chinese models. The U.S. should be competing, not seeking to ban them.
They treat AI models as files to be restricted or protected, ignoring the only scoreboard that matters: which models the grad students at Berkeley, Stanford, MIT and Carnegie Mellon reach for when they start an experiment.
Right now, the answer should alarm anyone who cares about American technological leadership….Chinese models overtook American ones in cumulative downloads in the summer of 2025 and have since opened a gap of more than 400 million. By early this year, 70% of all new fine-tuned models—the derivative works researchers and developers build on top of base models—were built on Chinese foundations.
The winner of a platform war is whoever captures the contribution loop—the self-reinforcing cycle in which researchers, toolmakers and downstream builders improve a platform.
China’s AI labs have internalized this lesson with remarkable discipline….Open-sourcing is how a nation exports its stack.
What is required for the U.S. to win? Five things, none of which is a ban….First, top-tier American models must be released openly and regularly…Fifth, government and industry alike should fund the shared plumbing of an open-weight environment—testing tools, public datasets, computing power for universities—so that building on American models is the easy choice, not an act of patriotism.
The demand for American open models is enormous. The supply isn’t.
The day the typical AI paper out of Stanford fine-tunes an American open model—simply because it is the best model available—is the day we are winning.