# If open weight models are the future, U.S. AI companies are going to have a hard time > Source: > Published: 2026-07-24 11:00:00+00:00 Top executives at leading Western [AI](https://www.fastcompany.com/section/artificial-intelligence) companies are increasingly warning about the safety and national security risks posed by Chinese open-weight frontier models. What they tend not to mention is that these models are improving rapidly and, because they are freely available, pose a serious threat to Western labs’ business models. The most powerful models from U.S. labs such as [OpenAI](https://www.fastcompany.com/section/open-ai), [Anthropic](https://www.fastcompany.com/section/anthropic), and [Google DeepMind](https://www.fastcompany.com/section/deepmind) are closed, meaning the parameters that shape their outputs are kept secret. Generative AI models contain layer upon layer of these parameters, commonly known as weights. During training, the model adjusts them to determine how strongly different pieces of information should influence its response. Working together, the weights allow the model to identify patterns and generate the most probable answer to a user’s prompt. The largest frontier models may contain a trillion parameters or more. Setting and fine-tuning those weights is enormously expensive, and their quality is a major factor separating a superior model from an inferior one. Western AI labs therefore guard them as closely held trade secrets. The model and its weights remain on the provider’s servers, while enterprise customers access its capabilities through an application programming interface (API). As long as closed models are clearly better than free, open-weight alternatives, companies may be willing to pay for API access. Customers don’t have to provide their own computing infrastructure or manage the model’s security and maintenance. They simply pay to access its intelligence and benefit from improvements as new versions are released. Labs such as OpenAI and Anthropic, meanwhile, face enormous costs for computing power, training data, and research talent. Their businesses depend on API fees and consumer subscriptions to help offset those expenses. Both companies are also widely expected to pursue public offerings in the coming years. By mid-2026, however, open-weight frontier models from Chinese labs such as [Alibaba](https://www.fastcompany.com/section/alibaba), [DeepSeek](https://www.fastcompany.com/section/deepseek), and [Moonshot AI](https://www.fastcompany.com/91577355/kimi-k3-china-ai-trump) had nearly matched the leading Western models in intelligence and performance. Many companies have already begun building their AI systems on top of these free models, avoiding the high cost of closed-model APIs. Because businesses can host open-weight models in their own private [clouds](https://www.fastcompany.com/91411810/your-data-may-be-in-the-cloud-but-that-doesnt-mean-its-safe), they can also avoid sending proprietary data to systems controlled by outside providers. Developers can fine-tune the models for specific needs, build applications and tools on top of them, and optimize them for their preferred infrastructure. When thousands of companies adopt the same model, its creator gains influence even without charging directly for access. The strategy resembles Google’s decision to make Android broadly available to device manufacturers, while Apple kept iOS exclusive to its own hardware. Some open-weight developers generate revenue by helping enterprise customers fine-tune, deploy, and build applications around their models. Chinese AI labs also have their own reasons for releasing model weights. Because they often lack the research budgets and computing resources of their Western rivals, they can benefit from improvements made by developers around the world. Widely adopted open-weight models can also increase demand for the broader Chinese AI ecosystem, including domestic chips, cloud platforms, and developer tools.