Hugging Face CEO: The real AI race may no longer be at the frontier as open models reshape the industry

While the AI industry spent weeks fixated on Anthropic's latest frontier models and Washington's fight to control access to them, developers kept building — and they weren't waiting for permission from the Anthropics and OpenAIs of the world, according to a TechCrunch report featuring Hugging Face CEO Clem Delangue.

Data underscores the shift. Chinese open-weight models accounted for 41% of downloads on Hugging Face this spring, surpassing US models. On OpenRouter, the top six most popular models are all open models from Chinese firms including Tencent, Xiaomi, DeepSeek, MiniMax, and Z.ai. Anthropic's Claude Opus 4.7 trails in seventh place. Data from Vercel shows open-weight models handled nearly a third of AI requests on the platform in June, absorbing volume-heavy AI infrastructure while closed models operate as a higher-cost premium layer.

Delangue said this raises a difficult question: How much do frontier models still matter if most production AI ends up running on cheaper, customizable alternatives? "Maybe in a few years, the frontier models will be for experimenting and for some really high-value tasks, and most of the production workloads will actually be powered either by private models within companies or by open source models," he said.

Hugging Face, a platform for hosting, sharing, and deploying open models, is at the center of this shift. Delangue says customers and community members increasingly tout the benefits of owning their own AI models rather than renting them, a trend that accelerated after companies saw the bills associated with scaling closed frontier models. A new repository is created every seven seconds on the platform, which hosts nearly three million public models and one million public datasets. Half of all Fortune 500 firms use Hugging Face to deploy their own private and open source models.

"If you're an AI company or a technology company, you don't want to outsource your core capabilities to another company, to a black box API that you don't control, don't have any visibility on, and don't really have any sort of ownership," Delangue said.

Every few months, another Chinese AI company releases a powerful open-weight model that is cheaper to deploy and easier to customize than closed competitors. Most recently, Beijing-based Z.ai released GLM-5.2, an open-weight model that excels at agentic coding and competes with Anthropic's latest models on identifying security vulnerabilities.

Delangue isn't alone in arguing that enterprises should avoid single-provider lock-in. Microsoft CEO Satya Nadella recently warned against this, arguing that control of data should be a primary concern. However, the rise of open models has intensified debate over safety risks. Anthropic CEO Dario Amodei has argued that scaling powerful open model weights could become dangerous as they are hard to control once released.

Delangue sees the tradeoff differently. "The biggest risk in AI is concentration of power," he said. "The way you make the world safer, in my opinion, is by leveling up the playing fields and creating transparency on these models." He argued that restricting powerful models simply concentrates technology in a few companies while reducing transparency, and that it's already possible to bypass frontier model API guardrails and steal weights.