Zixuan Li, Head of Zhipu (Z.ai): Open Weights Are Not a Concession, But a Business Strategy Aligned with Customer Needs
At the AI Engineer World's Fair, Zixuan Li explained why Zhipu (Z.ai) released GLM-5.2, a model with capabilities near the frontier, as open weights. His core argument is not technical idealism but the alignment of three parties' needs: enterprises and governments require local deployment for security and control; companies in legal, financial, and security sectors need fine-tuning to achieve differentiation; and deep users need visibility into architecture and training recipes to co-design the future. These three paths correspond to Zhipu’s needs for gaining trust, expanding model potential, and making correct investment judgments.
At the AI Engineer World's Fair in September 2026, Zixuan Li, head of Zhipu (Z.ai), faced a question he was repeatedly asked: Why release a model with near-frontier capabilities as open weights? He directly acknowledged the subtext of the question: Does releasing near-frontier models as open weights mean handing the market over to inference service providers?
Li broke down the open-weight decision into three aligned sets of needs. The first set is security and control. He stated that if enterprises or governments—particularly institutions in the Western world—want to use the model, Zhipu uploads the weights to Hugging Face so they can run it on their own servers. This changes who operates the model and gives customers more control over deployment. He explicitly described this as a deployment option, not a completed installation or a verified security outcome.
The second set is diversity, or domain-specific customization. Customers in the legal, financial, and security fields need different model behaviors, which requires access to weights for fine-tuning. He cited Harvey, a legal AI company, as an example; Harvey is already fine-tuning GLM-4.1 and may next consider fine-tuning GLM-5.2. However, Li framed Harvey’s shift to 5.2 as a 'possibility' rather than a completed adoption. He also mentioned speaking with many other companies that are considering fine-tuning GLM as a differentiation strategy.