China's AI Coding Tool Zhipu Quietly Wins Over US Developers

American developers have a confession to make: they're quietly using Chinese AI tools. And they like what they see.

Zhipu AI's GLM 4.7 coding model is gaining unexpected traction in the United States, marking a potential shift in how developers view Chinese artificial intelligence. The Shanghai-based startup recently announced it would limit access to its coding tool due to overwhelming demand—with its investor relations team confirming that "the user base is primarily concentrated in the United States and China."

This revelation comes at a critical moment. Just a year after DeepSeek's R1 model rattled Silicon Valley, and weeks after American tools like Replit and Claude Code demonstrated seemingly frontier-level capabilities, a Chinese competitor is quietly building momentum on American soil.

The Bias That's Breaking Down

For years, American developers have expressed skepticism about Chinese AI models, citing concerns about data privacy, government influence, and technical capabilities. This bias has kept Chinese tools largely confined to their domestic market, even as companies like ByteDance and Alibaba invested billions in AI research.

But Zhipu's growing US user base suggests something fundamental is shifting. When CNBC tested the tool against American counterparts, asking it to build a tracker for China's biggest public companies, Zhipu delivered results faster than its US competitors—though with less polished output.

The speed advantage isn't trivial. In a market where Replit and Claude are already driving a 60% surge in new app releases, developers are increasingly prioritizing rapid prototyping over perfect aesthetics. If a Chinese tool can match or exceed that velocity while offering open-source accessibility, traditional competitive advantages start to erode.

The Recognition Factor

Tuhin Srivastava of Baseten, a platform that processes AI workloads across enterprises, confirms he's seeing Zhipu in real-world testing scenarios. This matters because Baseten recently secured funding with Nvidia participation, positioning it as a reliable gauge of which models are gaining serious enterprise attention.

The mixed reviews Srivastava and others report aren't necessarily damaging. Early adoption of any AI tool involves trade-offs, and developers are increasingly willing to experiment with models that offer different strengths—especially when they're free or significantly cheaper than American alternatives.

Google DeepMind's Demis Hassabis recently claimed Chinese AI is "six months behind" Western capabilities. But if Zhipu can deliver comparable coding results at lower costs, that timeline gap may be less relevant than the price and accessibility gap.

The Open Source Advantage

Unlike many American AI models that remain proprietary, Chinese companies like Zhipu often embrace open-source approaches. This strategy serves multiple purposes: it accelerates adoption, builds developer loyalty, and creates network effects that can quickly establish market presence.

For American companies that have invested heavily in closed systems and premium pricing models, this presents a strategic challenge. How do you compete with "good enough" technology that's freely available and rapidly improving?

The answer may lie in specialization and integration. While Zhipu excels at speed, American tools still lead in polish, user experience, and ecosystem integration. The question is whether those advantages justify the premium as Chinese alternatives continue improving.