China’s AI models spooked Wall Street. But they may turbocharge industry growth

Chinese AI models have recently caused concern for US investors, but some analysts argue that falling model costs will ultimately benefit the AI industry by driving global demand for AI systems. In recent weeks, large-language model (LLM) inference prices per million tokens have dropped from above US$2 at the beginning of June to just US$1.2, according to research firm Silicon Data's LLM Token Expenditure Index.

This price drop has prompted major US firms, such as OpenAI, to slash the prices of their closed models in a bid to gain market share. For example, OpenAI recently offered an 80% discount on developer pricing for its lightweight GPT-5.6 Luna model and a 20% discount on the mid-tier GPT-5.6 Terra. While this has fueled a sell-off in AI stocks last month due to concerns about overvaluation among US hyperscalers, analysts argue that competition among Chinese and American LLM developers will benefit the industry in the long run.

Morgan Stanley's Stephen Byrd noted that the pursuit of efficiency by both Chinese and American developers could lead to vastly higher demand for compute resources beyond supply. According to Morgan Stanley, competition between open-weight models and closed systems could result in three possible outcomes: open-weight models prevailing, closed systems dominating, or a hybrid scenario where both coexist.

In all three scenarios, cloud service providers like Microsoft, Amazon, and Google are expected to benefit. US tech stocks have rebounded following strong results from cloud giants Microsoft and Amazon, which reported double-digit growth in their cloud services. However, some analysts argue that the rise of cheaper Chinese open-weight AI could threaten the monetization potential of US cloud giants, as routine inference could be routed to cheaper Chinese models, leading to lower revenue per unit of demand.