- Nvidia CEO Jensen Huang Warns of China’s Big Advantages in AI
- This is the rapid realization of data center construction and China’s strong energy infrastructure to meet the energy needs of AI.
- Meanwhile, a new study finds that Chinese open-source LLMs have driven nearly a third of global AI use.
Nvidia Chief Executive Officer Jensen Huang once again warned of the rapid progress China is making in AI and the advantages the country has in terms of development infrastructure.
Fortune reports that late last month, Huang spoke with John Hamre, president of the Center for Strategic and International Studies (CSIS), noting that: “If you want to build a data center here in the United States, from start to finish, [an] The AI supercomputer will probably be around three years old. They [China] can build a hospital in a weekend.
In other words, China is capable of completing large construction projects at incredibly fast speeds and also has a major advantage in energy infrastructure.
These are crucial elements for AI development because it’s about quickly building huge data centers, meeting processing needs, and having the energy to power it all.
Huang observed that China has “twice as much energy as we do.” [the US] that we have as a nation, and our economy is bigger than theirs” and that this “makes no sense to me”, and further that energy capacity growth is going “straight up” in China, while it remains more or less stable in the United States.
However, to counterbalance the concerns expressed, the CEO made it clear that Nvidia is “generations ahead” of China when it comes to AI chip technology – there may be a tiny bit of bias in that claim, but Huang still said that’s no reason to rest on laurels.
Huang has previously said China is “nanoseconds behind America” in the AI race, but we’re told the Nvidia CEO remains outwardly optimistic about the Trump administration’s efforts to boost AI investment and domestic manufacturing jobs.
Symbolic efforts and rapid rise
At the same time, a separate article in the South China Morning Post (SCMP) claims that almost 30% of global AI use now comes from Chinese open source models (LLM).
This figure comes from a report compiled by OpenRouter, an independent aggregator of AI models, in collaboration with venture capital firm Andreessen Horowitz. It is based on a study of 100 trillion tokens, which are the units of data processed by LLMs (or, in friendlier language, the building blocks of how AI works).
The lion’s share goes to closed-source Western LLMs, like ChatGPT, which hold the rest of the market (around 70%).
Remember though, just a year ago, Chinese open source LLMs accounted for just over 1% of tokens, so reaching 30% today is a pretty steep growth trajectory to say the least.
If we take only open source LLMs, we are told that Chinese models on average account for around 13% of weekly token usage, which is almost equivalent to the rest of the world’s 13.7%. (This is open source, remember – the remaining majority are closed proprietary models like ChatGPT).
Another interesting point revealed here is that open source LLMs from China are now also doing their part, it’s not just about DeepSeek (as it was originally). Naturally, DeepSeek V3 is a major force in China’s use of AI, but there are also Alibaba’s Qwen and Moonshot AI’s Kimi K2 that are big players.
The report claims that Chinese language prompts are now second in token volume behind English.
Putting all this together, then, China’s rise in AI is a rather dizzying climb, and you can see where Huang’s concerns come from. Especially since it’s hard to imagine a slowdown in this growth in the near term for China, and what Nvidia’s CEO is observing about the country’s energy infrastructure is indeed a telling advantage over the United States – again, hard to see changing in the near future.
And then, as we’ve seen recently with the release of DeepSeek’s new v3.2 models, there’s what China has to offer in terms of reducing the costs of using AI, to boot. It appears that a serious competitive battle is brewing for global AI dominance.
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