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A former ByteDance engineer says China's AI industry is 'far behind' the US — and the gap is getting worse

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A former ByteDance LLM engineer and Peking University professor claims China’s AI gap with the U.S. is widening, contradicting industry narratives about rapid Chinese progress. Chinese AI models excel in benchmarks but fail in real-world applications due to "benchmaxxing"—prioritizing test scores over practical performance, per Zhang Chi’s firsthand observations. U.S. firms like Google iterate AI models in months, while Chinese companies take twice as long, slowing innovation and limiting competitive edge in deployment speed. Structural hurdles—chip restrictions, weaker infrastructure, and low-quality training data—hinder China’s progress, with some firms relying on distilled U.S. model outputs rather than original development. Weak user feedback loops trap Chinese models in a cycle of underperformance, as low adoption stifles improvement, while U.S. models like ChatGPT refine continuously through real-world interactions.
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A former ByteDance engineer says China's AI industry is 'far behind' the US — and the gap is getting worse

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Zhang Chi, a former ByteDance LLM engineer, says China's AI is falling further behind the US. Qilai Shen/Bloomberg via Getty Images 2026-04-24T11:08:30.443Z Share Copy link Email Facebook WhatsApp X LinkedIn Bluesky Threads lighning bolt icon An icon in the shape of a lightning bolt.

Impact Link Save Saved Read in app This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Log in. A former ByteDance engineer says China's AI industry is still far behind the US. Zhang Chi said China's model benchmarks perform well but don't translate into real-world results. Tech leaders like Elon Musk and Jensen Huang believe China is catching up and could even pull ahead. AI-generated summary Summaries are generated by an AI model trained on Business Insider's articles. AI may make mistakes or provide inaccurate/incomplete information. We're unable to load that answer right now. Please try again. How do US and China AI models differ? Why is user feedback crucial in AI? What role do advanced chips play in AI? What structural disadvantages does China face? How does 'benchmaxxing' impact real-world AI? For all the talk that China is catching up to the US in AI, a former ByteDance engineer believes it's actually falling further behind. Loading audio narration... "I don't even agree with the assumption that Chinese models are catching up — I believe we're still far behind," Zhang Chi, a research scientist and assistant professor at Peking University, said on an episode of the "Into Asia" podcast. "I guess the gap is getting larger, very sadly."Zhang, who said he spent about a year at ByteDance working on AI models before returning to academia, said the differences go beyond the perceived rapid progress of Chinese startups. While models from companies like ByteDance, TikTok's parent company, and Alibaba may score well on benchmarks, he said that doesn't mean they work as well in the real world."On paper, every big tech company in China has a good model," Zhang said. "But I don't think they're good enough." He added that many teams are focused on "benchmaxxing" — optimizing for test scores rather than practical performance. ByteDance and Alibaba have rolled out high-profile AI models — from video generators like Seedance to open-source systems like Qwen — but they've also faced backlash over deepfakes, copyright disputes, and whether those models hold up in real-world use.A key issue, Zhang said, is speed. He said top US companies can iterate on models far more quickly. "Google can train or perform a full round of LLM training, both pre-training and post-training, in three months," he said. "But ByteDance — probably we can only do one iteration in half a year."Zhang also pointed to China's structural disadvantages, including access to advanced chips, weaker infrastructure, and lower-quality training data. "There's a huge difference between the infrastructure at Google and ByteDance," he said. "I don't think we're getting high-quality data."He added that some companies rely on distilling outputs from leading US models rather than building their own data pipelines — a shortcut that may limit long-term progress. Zhang said US firms also benefit from stronger user feedback loops. Products like ChatGPT, Claude, and Gemini improve through constant interaction with users, which helps refine their models over time.Chinese models, by contrast, risk falling into a negative cycle. "Chinese models started not as good, so no one really uses them for really important things," Zhang said. "And the models continue to be not that good." Others say China is catching upZhang's view contrasts sharply with some of the most prominent voices in tech, many of whom say China is rapidly closing the gap and could even pull ahead.Nvidia CEO Jensen Huang has warned that the US risks falling behind, while Elon Musk has said that China's advantage in energy and compute could help it overtake rivals. AI pioneer Geoffrey Hinton has also said the US lead may be narrower than it appears, cautioning it could erode over time.Others take a more nuanced view. Alibaba chairman Joe Tsai has said the race will be decided less by model strength and more by how quickly AI is deployed. Still, Zhang's assessment reflects a more pessimistic perspective from inside China's AI ecosystem — one that suggests the gap with the US may be widening."To be fair, I don't think any Chinese company can catch up with them soon," he said.

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