By limiting access to top-tier proprietary models, U.S. policy may have ironically forced China to develop more efficient, open-source alternatives. This strategy is more effective for global adoption, as other countries can freely adapt these models without API limits or vendor lock-in.

While US firms lead in cutting-edge AI, the impressive quality of open-source models from China is compressing the market. As these free models improve, more tasks become "good enough" for open source, creating significant pricing pressure on premium, closed-source foundation models from companies like OpenAI and Google.

Joe Tsai reframes the US-China 'AI race' as a marathon won by adoption speed, not model size. He notes China’s focus on open source and smaller, specialized models (e.g., for mobile devices) is designed for faster proliferation and practical application. The goal is to diffuse technology throughout the economy quickly, rather than simply building the single most powerful model.

The emergence of high-quality open-source models from China drastically shortens the innovation window of closed-source leaders. This competition is healthy for startups, providing them with a broader array of cheaper, powerful models to build on and preventing a single company from becoming a chokepoint.

Counterintuitively, China leads in open-source AI models as a deliberate strategy. This approach allows them to attract global developer talent to accelerate their progress. It also serves to commoditize software, which complements their national strength in hardware manufacturing, a classic competitive tactic.

Unable to compete globally on inference-as-a-service due to US chip sanctions, China has pivoted to releasing top-tier open-source models. This serves as a powerful soft power play, appealing to other nations and building a technological sphere of influence independent of the US.

Instead of military action, China could destabilize the US tech economy by releasing high-quality, open-source AI models and chips for free. This would destroy the profitability and trillion-dollar valuations of American AI companies.

Z.AI and other Chinese labs recognize Western enterprises won't use their APIs due to trust and data concerns. By open-sourcing models, they bypass this barrier to gain developer adoption, global mindshare, and brand credibility, viewing it as a pragmatic go-to-market tactic rather than an ideological stance.

While the U.S. leads in closed, proprietary AI models like OpenAI's, Chinese companies now dominate the leaderboards for open-source models. Because they are cheaper and easier to deploy, these Chinese models are seeing rapid global uptake, challenging the U.S.'s perceived lead in AI through wider diffusion and application.