Uncertainty swirls around chip sales to China, despite Huang’s Beijing trip
Nvidia founder and CEO Jensen Huang waves after a welcome ceremony for US President Donald Trump at the Great Hall of the People in Beijing on May 14, 2026.
Brendan Smialowski | Afp | Getty Images
One big area of uncertainty is China, specifically pertaining to Nvidia’s older Hopper GPU, known as H200. Huang was a last-minute addition to President Donald Trump’s China summit last week, but the visit did little to clear up whether H200 sales will be permitted in the country.
Huang said at Nvidia’s GTC conference in March that Nvidia had received H200 orders from China.
“We’re in the process of restarting our manufacturing,” Huang told reporters at the event in San Jose, California.
Reuters reported last week that a handful of Chinese companies have been approved by the U.S. Commerce Department to purchase H200s, including Alibaba, Tencent, ByteDance and JD.com.
But one U.S. trade representative said chip export controls were not discussed in the China talks last week, suggesting a major breakthrough on H200 sales may not be close.
China once accounted for at least one-fifth of Nvidia’s data center revenue, but the company has been shut out of the country since being told by the Trump administration in April that it would require a license to export chips there and to a handful of other countries.
—Katie Tarasov
Cerebras’ blockbuster IPO signals new chip competition
Cerebras Systems‘ monster Nasdaq debut last week was a clear signal that tech giants are hungry for alternatives to Nvidia’s costly (and sold out) GPUs. The company’s market cap swelled to almost $100 billion on its first day of trading.
Cerebras makes a different type of chip, known as a custom ASIC — application-specific integrated circuit — that’s been gaining ground as agentic AI shifts compute needs toward inference. While GPUs excel at the parallel math necessary for training large models, inference can happen on less powerful chips programmed for more specific tasks.
It’s an increasingly crowded space, with in-house ASICs now made by the likes of Google, Amazon, Meta and Microsoft. Cerebras operates its dinner-plate-sized chips inside its own data centers, pitting it against cloud providers Google, Microsoft, Oracle and CoreWeave.
Nvida also makes custom ASICs in-house after spending $20 billion to acquire Groq’s technology in December, and then announcing custom Groq Language Processing Units at GTC in March.
—Katie Tarasov
Nvidia hit $5 trillion in October. How long until $6 trillion?
Nvidia’s stock is up roughly 20% so far this year, underperforming many of its semiconductor peers but still enough of a gain to support the biggest market cap in the world.
Nvidia became the first $5 trillion company in October, and inched closer to reaching the $6 trillion record last week, though after a bit of a pullback the number now sits at $5.5 trillion.
The company’s record-breaking run comes as chip companies not named Nvidia hit historic highs. Intel had its best month ever in April, as agentic AI spins up a major renaissance for the central processing unit. Memory makers like Micron, meanwhile, have seen shares surge amid a shortage for the key type of chip needed to support AI.
Alphabet briefly surpassed Nvidia to become the world’s most valuable company in after-hours trading earlier this month, but for now that appears to be a momentary blip. Google’s parent is currently worth about $4.6 trillion.
—Katie Tarasov
Nvidia’s data center business is booming as tech giants ramp up AI spending
Nvidia has been a leading beneficiary of the AI boon due to its graphics processing units, or GPUs, that are used to train and run powerful foundation models.
Data center revenue for Nvidia’s fiscal first quarter is expected show an 87% increase from a year earlier to $73.1 billion, representing even faster expansion than the 75% year-over-year jump in the prior quarter and 73% growth rate in the same period a year ago.
The persistent growth reflects the exploding capital expenditures from hyperscalers, which are snapping up GPUs for their data center computing infrastructure that underpins their AI initiatives.
On the same day last month, Alphabet, Amazon, Meta and Microsoft all reported quarterly results, giving investors an updated glimpse into their capex forecasts for the year. Financial firms like Evercore and Bank of America are projecting the group will spend over $1 trillion on AI-related capex in 2027, which ultimately benefits Nvidia.
John Belton, portfolio manager at Gabelli Funds, said in an email on Tuesday that he’s “looking for whether the company is broadening its customer base as that remains a major risk,” adding that five names account for roughly half of Nvidia’s business.
“I’m questioning things such as how durable the growth within that segment of the business is as well as if they’re expanding the customer base and broadening the product set,” Belton said.
