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America’s Open-Model Paradox

Sequoia By Dean Meyer and Konstantine Buhler Covered by 75 sources

America’s use of Chinese open models has become a major dependency chain for Western AI startups and labs, including using Chinese models as teachers and synthetic-data sources for post-training. In ATOM’s Report, Qwen’s share of new open-model fine-tunes and adaptations rose from 1% in January 2024 to 69% by February 2026. The article argues this dependence should be replaced with a lawful domestic “teacher” route and added enforcement to raise the cost of foreign distillation, so Western firms can build cheaper, ownable models without relying on China’s open layer.

Why it matters

To Distill, or Not to Distill?

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