- Nvidia CEO Jensen Huang has warned of China’s big advantages in AI
- It is the rapid realization of the construction of data centers and China’s robust energy infrastructure to support AI’s energy needs
- Meanwhile, a new study has found that China’s open source LLMs have secured nearly a third of global AI use
Nvidia CEO Jensen Huang has again warned about the rapid progress China is making in AI and the advantages the country has in terms of the infrastructure for development therein.
Fortune reports that late last month, Huang spoke with John Hamre, the 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 breaking down to standing up. [an] AI supercomputer is probably about three years. The [China] can build a hospital in a weekend.”
In other words, China is able to realize large construction projects at incredibly fast speeds and also has a great advantage in terms of its energy infrastructure.
These are crucial elements for the development of AI in terms of building huge data centers quickly, to cope with processing needs and having the energy to power all of this.
Huang noted that China has “twice as much energy as us [the US] have as a nation, and our economy is bigger than theirs,” and that this “doesn’t make sense to me,” and further that energy capacity growth is “straightening up” in China, while remaining roughly flat in the United States.
To balance the concerns raised, however, the CEO made it clear that Nvidia is “generations ahead” in China when it comes to AI chip technology – there may be a little bit of bias in that claim, but Huang still said this was no reason to rest on our laurels.
Huang has previously commented that China is “nanoseconds behind the US” in the AI race, but we’re told the Nvidia boss remains outwardly hopeful about the Trump administration’s push to increase AI investment and domestic manufacturing jobs.
Token effort and a quick ascent
Meanwhile, a separate article from the South China Morning Post (SCMP) claims that nearly 30% of global AI use now comes from China’s open source models (LLMs).
That number comes from a report compiled by OpenRouter, an independent AI model aggregator, along 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 remains with the closed source Western world LLMs, such as ChatGPT, which hold the rest of the market (around 70%).
However, keep in mind that just a year ago Chinese open source LLMs represented just over 1% of tokens, so reaching 30% now is a pretty steep growth trajectory to say the least.
If you only take open source LLMs, we are told that Chinese models average about 13% of weekly token usage, which is almost the same as the 13.7% that is taken from the rest of the world. (This is open source usage, remember – the remaining majority are the proprietary closed sources like ChatGPT).
Another interesting point revealed here is that the open source LLMs from China are now pulling their weight, it’s not just about DeepSeek (as was the case initially). Of course DeepSeek V3 is a major force in AI usage for China, but there are also Alibaba’s Qwen models and Moonshot AI’s Kimi K2 which are big players.
The report claims that Chinese prompts are second in token volume after English now.
When all of this is tied together, China’s progress in the AI sphere is a pretty staggering rise, and you can see where Huang’s concerns come from. Especially since it’s hard to see this growth slowing down in the near term for China, and what Nvidia’s CEO observes about the country’s energy infrastructure is actually a telling advantage over the US – again, one that’s 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 cost of using AI, to boot. It looks like there is a seriously competitive battle ahead for global AI dominance.
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