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Banned Nvidia Chips Available in China’s Underground Markets

Shops in Shenzhen’s famous electronics market are selling high-end Nvidia chips, but the costs are huge and the numbers appear to be limited

Shenzhen's SEG Plaza has shops crammed with electronic goods, even sanctioned Nvidia chips (Reuters).


US export restrictions on high-end computer chips have created an underground market in China in which vendors are charging huge mark-ups for top-end Nvidia AI chips.

At the Huaqiangbei electronics area in the southern tech hub of Shenzhen, shops in the SEG Plaza skyscraper cater for camera parts to drones, and chips can also be quietly sourced.

Two vendors, who spoke on condition of anonymity, said they could provide small numbers of A100 artificial intelligence chips made by Nvidia, the US chip designer, at $20,000 a piece – double the usual price.

While buying or selling high-end US chips is not illegal in China, US export restrictions have created a de facto underground market, but vendors are keen not to draw scrutiny from either US or Chinese authorities.


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President Joe Biden’s administration in September ordered Nvidia to stop exporting its two most advanced chips – the A100 and the recently developed H100 – to mainland China and Hong Kong, as part of efforts to stymie Chinese AI and supercomputing development amid intensifying political and trade tensions.

That was then followed up with an array of semiconductor-related export controls.

But, as AI booms across the globe after the runaway success of OpenAI’s ChatGPT, demand for high-end chips has rocketed, particularly for Nvidia’s microprocessors, which are widely regarded as the best at handling machine-learning tasks.

“We are talking with two vendors now to get some,” said Ivan Lau, co-founder of Hong Kong’s Pantheon Lab, who is trying to purchase 2-4 new A100 cards to run the startup’s latest AI models.

Those vendors, who bought the chips outside the US, were quoting HK$150,000 ($19,150) per card, he said, adding: “They told us straight up that there will be no warranty or support.”

Reuters spoke with 10 vendors in Hong Kong and mainland China who described being able to easily procure small numbers of A100s.

Their information highlighted both intense demand in China for the chips and the relative ease with which Washington’s sanctions can be circumvented for small-batch transactions.

But it was not possible to estimate overall volumes of Nvidia A100 and H100 chips flowing into China or learn to what extent the transactions taking place go towards satisfying demand.


Steady demand even for slower chips

Buyers are typically app developers, startups, researchers or gamers, the vendors said, declining to be identified because the imports contravene US trade restrictions. One vendor said buyers also included Chinese local authorities.

Nvidia said in a statement it did not allow exports of the A100 or H100 to China, instead providing reduced-capability substitutes that comply with US law.

“If we receive information that a customer is breaching their agreement with us and exporting restricted products in violation of the law, we would take immediate and appropriate action,” the statement said.

The US Department of Commerce, China’s State Council Information Office and China’s industry ministry did not respond to requests for comment.

Nvidia said in September that $400 million in sales during its third quarter could be lost if Chinese firms decided not to buy alternative Nvidia products.

Its new China-tailored slower variants – the A800 and H800 – developed to cushion that impact are now being bought by large Chinese tech firms such as Tencent Holdings and Alibaba, which have deep pockets to purchase huge quantities.


Supplies available via India, Taiwan, Singapore

The Chinese vendors said they procured the chips primarily in two ways: snatching up excess stock that finds its way to the market after Nvidia ships large quantities to big US firms, or importing through companies locally incorporated in places such as India, Taiwan and Singapore.

This means the quantities they can secure are small, far from what’s needed to build a sophisticated AI large language model from scratch.

A model similar to OpenAI’s GPT would require more than 30,000 Nvidia A100 cards, according to research firm TrendForce. But a handful can run complex machine-learning tasks and enhance existing AI models.

According to an electronics procurement website that listed some 40 sellers of A100s, most were located in the Huaqiangbei electronics area.

But listings for A100s could also be found on Alibaba’s Taobao e-commerce site, on Xiaohongshu which is similar to Instagram, as well as on Douyin, the Chinese version of TikTok.

Alibaba, Xiaohongshu and Douyin-owner ByteDance did not respond to requests for comment.

Some of the vendors cautioned that fraud had become common with refurbished chips being passed off as A100s.

Nvidia’s more advanced H100 chips, only on the market since March, appear much harder to come by.

Vinci Chow, a lecturer in economics at the Chinese University of Hong Kong whose department has procured four A100 cards from local vendors for research purposes, said he had been told some packs of eight H100 chips were available for purchase. But only one of the 10 vendors Reuters spoke with said they could procure H100s.

The US is likely not too bothered about small transactions of the chips, Charlie Chai, a Shanghai-based analyst at 86Research, said.

“Only if or when China poses a greater threat following significant catch-ups will we see more strict enforcement,” he said.

He believed the premiums currently commanded by Chinese vendors for A100 and H100 chips could collapse in the future as many of the Chinese AI startups that were driving purchases would eventually withdraw from the market.


  • Reuters with additional editing by Jim Pollard




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Jim Pollard

Jim Pollard is an Australian journalist based in Thailand since 1999. He worked for News Ltd papers in Sydney, Perth, London and Melbourne before travelling through SE Asia in the late 90s. He was a senior editor at The Nation for 17+ years.


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