DoorDash, startups turn to cheaper Chinese AI models as U.S. rivals get pricier

The shift toward cheaper Chinese AI models reflects a fundamental tension in the AI market: while U.S. companies have developed some of the world's most advanced models, their rising costs are creating an opening for alternatives. As token and usage fees increase, cost-conscious businesses are exploring options that offer acceptable performance at lower prices. The appeal is sharpened by the availability of open-source models that can run locally, addressing a genuine concern among companies that want to avoid sending proprietary data to external providers.

Yasir Atalan, deputy director of the Futures Lab at the Center for Strategic and International Studies, identifies three drivers: cost, capability, and open-source availability. The data supports the trend's real scale—a March 16, 2026 study from Hugging Face found that Chinese open-source models accounted for 41% of downloads. However, Atalan cautions against viewing this as a wholesale migration; companies are more likely experimenting by using different models for different tasks. This suggests a pragmatic division of labor: cheap, capable Chinese models for some workloads; established U.S. providers like Anthropic for others.

Yet the cost advantage comes with a significant tradeoff. Security experts raise serious concerns about data sovereignty and the risk of foreign surveillance when adopting Chinese models. The decision ultimately hinges on whether a model is "cheap and capable enough" to run locally, which means cost and performance may outweigh geopolitical concerns for many businesses—at least in the near term.