OpenFold's strategy isn't just to provide a free tool. By releasing its training code and data, it enables companies to create specialized versions by privately fine-tuning the model on their own proprietary data. This allows firms to maintain a competitive edge while leveraging a shared, open foundation.

Chinese AI leaders like Moonshot have lower valuations than US peers because they are often open-source. Unlike closed-source models (ChatGPT, Claude) that capture 100% of the value, open-source projects hope to capture just 10-20% through hosted services, leading to a "missing zero" in their funding rounds.

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.

Unlike the largely closed-source US market, DeepSeek's open-source models spurred intense competition among Chinese tech giants and startups to release their own open offerings. This has made Chinese open-source models the most used globally by token count, creating a distinct competitive dynamic.

The rise of Chinese AI models like DeepSeek and Kimmy in 2025 was driven by the startup and developer communities, not large enterprises. This bottom-up adoption pattern is reshaping the open-source landscape, creating a new competitive dynamic where nimble startups are leveraging these models long before they are vetted by corporate buyers.

Despite powerful open-source AI models, companies like Anthropic post record revenue. This indicates the total addressable market (TAM) is dramatically larger than anticipated, supporting both paid and open-source ecosystems simultaneously rather than one cannibalizing the other.

China isn't giving away its AI models out of generosity. By making them open source, it encourages widespread adoption and dependency. Once users are locked into the ecosystem, China can monetize it, introduce ads, or simply lock down future, more advanced versions, giving it significant strategic leverage.

A common misconception is that Chinese AI is fully open-source. The reality is they are often "open-weight," meaning training parameters (weights) are shared, but the underlying code and proprietary datasets are not. This provides a competitive advantage by enabling adoption while maintaining some control.

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.