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US ban on Chinese AI models could cost firms up to $12 billion yearly
An academic estimate based on OpenRouter usage data suggests migration to proprietary alternatives could add about $2.0 billion annually for users, with the wider US economy facing $3.0 billion to $12.0 billion depending on reliance.
A potential US ban on Chinese open weight artificial intelligence models could impose major costs on American businesses, with estimates reaching up to $12.0 billion per year, according to an analysis cited by SCMP Economy.
The calculation was attributed to Daniel Yue, an assistant professor at Georgia Institute of Technology’s Scheller College of Business, and drew on usage data from New York based OpenRouter, an LLM aggregator that lets developers switch models via a unified API.
Yue said that if OpenRouter users were forced to move from Chinese open weight models to top proprietary alternatives, they could face an additional annual bill of about $2.0 billion. The estimate was based on token usage and price gaps between open and closed models recorded from July 21 to 27.
The report cautioned the figures are an order of magnitude approximation rather than a definitive projection, noting limits in tracking usage outside centralized platforms, since OpenRouter captures only a fraction of the global LLM inference market. Extrapolated to the broader US economy, the cost increase could range from $3.0 billion to $12.0 billion depending on reliance on Chinese open weight models.