Who’s Afraid of Chinese Models?

Simon Willison · Simon Willison · 20 July 2026, 17:09 ● Covered by 8 sources

Ben Thompson proposes US legislation to establish data collection for model training as fair use and ban terms of service prohibiting model distillation, allowing open-source models to compete with Chinese alternatives. Alibaba released Qwen 3.8 Max as open weights after keeping Qwen 3.7 Max closed in May, possibly following Xi Jinping's recent remarks encouraging open-source development. The policy would indemnify AI labs while enabling wider innovation from collected training data and shift competitive dynamics in the global AI market.

Why it matters

Who’s Afraid of Chinese Models? Interesting proposal from Ben Thompson that both addresses the hypocrisy of labs outlawing distillation against their models despite training on unlicensed data, and could help US open models compete more effectively with their Chinese counterparts: The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation, for U.S. companies at a minimum. Stopping distillation — which is literally just querying the API — is nearly impossible; the U.S. should go the other way and lean into a new copyright policy that both indemnifies the labs and also guarantees that what they learned fuels further innovation for everyone else. Ben also theorizes that Alibaba's decision to release Qwen 3.8 Max as open weights - a reversal from their decision not to release Qwen 3.7 Max in May - may have been influenced by a recent speech by Xi Jinping, who said: We should seize this rare