Arm is preparing for a blockbuster initial public offering at a time when investors are very interested in both semiconductors and artificial intelligence.
Nvidia’s 200% rally this year is evidence of this. Arm is looking to raise nearly $5 billion from the IPO which would value it at over $50 billion. And demand is high with Reuters reporting that the company could price its shares at the top of its indicated range or possibly even above it.
Part of that may be down to Softbank, the owner of Arm, and its positioning of the British chip designer as an AI play. Arm will be “central” to the transition to AI-enabled computing, the company said in its IPO prospectus.
But the company is a different proposition to Nvidia and is unlikely to see the benefits of the AI boom in the near-term, analysts told CNBC.
Nvidia vs. Arm: A comparison
AI has been thrust into the spotlight, in large part thanks to OpenAI’s ChatGPT. This is a technology known as generative AI because the AI is able to generate answers in response to user prompts.
Such an AI is based on a model which is trained on huge amounts of data. A vast amount of computing power is required to train these AI models.
Nvidia designs a type of semiconductor called a graphics processing unit or GPU, which go into data centers to train and run these AI models.
Arm, meanwhile, is a company that designs the blueprint or “architectures” of certain semiconductors. These architectures are the overall designs, including components and programming language instructions that other companies use to build chips. Arm mainly designs central processing units or CPUs.
Arm-based CPUs are in 99% of the world’s smartphones including from major players like Apple.
While CPUs are also required in the data center, they’re often used in conjunction with a GPU to train data, but not always.
Arm makes most of its money from royalties and licensing its architecture. More than 50% of this revenue comes from smartphones and consumer electronics. So far, it is not seeing a big boost from AI.
“Growth in the near term for Arm is really not about AI, it’s about mobile, it’s about royalty increases,” Jamie Mills O’Brien, investment director at Abrdn, told CNBC’s “Street Signs Europe” on Monday.
“In the longer term, I think Arm is trying to focus investors minds on the potential … AI in the edge, AI in the data center, but at the moment that’s not a huge part of the company’s exposure.”
Arm’s future in AI
Arm’s AI future is unlikely to come from the huge amounts of chips required to train big data models.
Instead, it’s more likely to be a major player in AI on the “edge.” This phrase refers to AI processes carried out on a device, such as a smartphone, rather than in the cloud, like ChatGPT.
For this to happen, devices will require low-power but high-performance chips able to carry out the computing required for AI applications. Arm is designing the architecture for these chips.
“If you’re doing AI on a smartphone or car you’re not going to have that same level of compute power, so you need to optimize the model to run locally,” Peter Richardson, research director at Counterpoint Research, told CNBC.
“Those processors will almost certainly be Arm-based”
Arm said in its IPO filing that its processors already run AI workloads “and every smartphone currently in the market efficiently runs AI inference applications, such as voice recognition and applying filters to digital images.”
However, Arm is unlikely to see the benefit from AI filter through to its revenue for at least three-to-five years, Richard Windsor, founder of Radio Free Mobile, told CNBC.
What SoftBank has been required to do is to sell Arm as an AI company like Nvidia,” Windsor said.
“Now, in the long term absolutely, I’m a big proponent on running AI on end-devices, it makes an awful lot of economic sense for the provider of the service, and also much more in general in terms of the quality of the service, privacy and security and so on and so forth. But those revenues are not accruing to Arm right now.”
Co-founder and chief executive officer of Nvidia Corp., Jensen Huang attends the 9th edition of the VivaTech trade show in Paris on June 11, 2025.
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Nvidia CEO Jensen Huang has downplayed U.S. fears that his firm’s chips will aid the Chinese military, days ahead of another trip to the country as he attempts to walk a tightrope between Washington and Beijing.
In an interview with CNN aired Sunday, Huang said “we don’t have to worry about” China’s military using U.S.-made technology because “they simply can’t rely on it.”
“It could be limited at any time; not to mention, there’s plenty of computing capacity in China already,” Huang said. “They don’t need Nvidia’s chips, certainly, or American tech stacks in order to build their military,” he added.
The comments were made in reference to years of bipartisan U.S. policy that placed restrictions on semiconductor companies, prohibiting them from selling their most advanced artificial intelligence chips to clients in China.
Huang also repeated past criticisms of the policies, arguing that the tactic of export controls has been counterproductive to the ultimate goal of U.S. tech leadership.
“We want the American tech stack to be the global standard … in order for us to do that, we have to be in search of all the AI developers in the world,” Huang said, adding that half of the world’s AI developers are in China.
That means for America to be an AI leader, U.S. technology has to be available to all markets, including China, he added.
Washington’s latest restrictions on Nvidia’s sales to China were implemented in April and are expected to result in billions in losses for the company. In May, Huang said chip restrictions had already cut Nvidia’s China market share nearly in half.
Last week, the Nvidia CEO met with U.S. President Donald Trump, and was warned by U.S. lawmakers not to meet with companies connected to China’s military or intelligence bodies, or entities named on America’s restricted export list.
According to Daniel Newman, CEO of tech advisory firm The Futurum Group, Huang’s CNN interview exemplifies how Huang has been threading a needle between Washington and Beijing as it tries to maintain maximum market access.
“He needs to walk a proverbial tightrope to make sure that he doesn’t rattle the Trump administration,” Newman said, adding that he also wants to be in a position for China to invest in Nvidia technology if and when the policy provides a better climate to do so.
But that’s not to say that his downplaying of Washington’s concerns is valid, according to Newman. “I think it’s hard to completely accept the idea that China couldn’t use Nvidia’s most advanced technologies for military use.”
He added that he would expect Nvidia’s technology to be at the core of any country’s AI training, including for use in the development of advanced weaponry.
A U.S. official told Reuters last month that China’s large language model startup DeepSeek — which says it used Nvidia chips to train its models — was supporting China’s military and intelligence operations.
On Sunday, Huang acknowledged there were concerns about DeepSeek’s open-source R1 reasoning model being trained in China but said that there was no evidence that it presents dangers for that reason alone.
Huang complimented the R1 reasoning model, calling it “revolutionary,” and said its open-source nature has empowered startup companies, new industries, and countries to be able to engage in AI.
“The fact of the matter is, [China and the U.S.] are competitors, but we are highly interdependent, and to the extent that we can compete and both aspire to win, it is fine to respect our competitors,” he concluded.
Marek Antoni Iwanczuk | Sopa Images | Lightrocket | Getty Images
Google on Friday made the latest a splash in the AI talent wars, announcing an agreement to bring in Varun Mohan, co-founder and CEO of artificial intelligence coding startup Windsurf.
As part of the deal, Google will also hire other senior Windsurf research and development employees. Google is not investing in Windsurf, but the search giant will take a nonexclusive license to certain Windsurf technology, according to a person familiar with the matter. Windsurf remains free to license its technology to others.
“We’re excited to welcome some top AI coding talent from Windsurf’s team to Google DeepMind to advance our work in agentic coding,” a Google spokesperson wrote in an email. “We’re excited to continue bringing the benefits of Gemini to software developers everywhere.”
The deal between Google and Windsurf comes after the AI coding startup had been in talks with OpenAI for a $3 billion acquisition deal, CNBC reported in April. OpenAI did not immediately respond to a request for comment.
The move ratchets up the talent war in AI particularly among prominent companies. Meta has made lucrative job offers to several employees at OpenAI in recent weeks. Most notably, the Facebook parent added Scale AI founder Alexandr Wang to lead its AI strategy as part of a $14.3 billion investment into his startup.
Douglas Chen, another Windsurf co-founder, will be among those joining Google in the deal, Jeff Wang, the startup’s new interim CEO and its head of business for the past two years, wrote in a post on X.
“Most of Windsurf’s world-class team will continue to build the Windsurf product with the goal of maximizing its impact in the enterprise,” Wang wrote.
Windsurf has become more popular this year as an option for so-called vibe coding, which is the process of using new age AI tools to write code. Developers and non-developers have embraced the concept, leading to more revenue for Windsurf and competitors, such as Cursor, which OpenAI also looked at buying. All the interest has led investors to assign higher valuations to the startups.
This isn’t the first time Google has hired select people out of a startup. It did the same with Character.AI last summer. Amazon and Microsoft have also absorbed AI talent in this fashion, with the Adept and Inflection deals, respectively.
Microsoft is pushing an agent mode in its Visual Studio Code editor for vibe coding. In April, Microsoft CEO Satya Nadella said AI is composing as much of 30% of his company’s code.
The Verge reported the Google-Windsurf deal earlier on Friday.
Jensen Huang, CEO of Nvidia, holds a motherboard as he speaks during the Viva Technology conference dedicated to innovation and startups at Porte de Versailles exhibition center in Paris, France, on June 11, 2025.
The sale, which totals 225,000 shares, comes as part of Huang’s previously adopted plan in March to unload up to 6 million shares of Nvidia through the end of the year. He sold his first batch of stock from the agreement in June, equaling about $15 million.
Last year, the tech executive sold about $700 million worth of shares as part of a prearranged plan. Nvidia stock climbed about 1% Friday.
Huang’s net worth has skyrocketed as investors bet on Nvidia’s AI dominance and graphics processing units powering large language models.
The 62-year-old’s wealth has grown by more than a quarter, or about $29 billion, since the start of 2025 alone, based on Bloomberg’s Billionaires Index. His net worth last stood at $143 billion in the index, putting him neck-and-neck with Berkshire Hathaway‘s Warren Buffett at $144 billion.
Shortly after the market opened Friday, Fortune‘s analysis of net worth had Huang ahead of Buffett, with the Nvidia CEO at $143.7 billion and the Oracle of Omaha at $142.1 billion.
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The company has also achieved its own notable milestones this year, as it prospers off the AI boom.
On Wednesday, the Santa Clara, California-based chipmaker became the first company to top a $4 trillion market capitalization, beating out both Microsoft and Apple. The chipmaker closed above that milestone Thursday as CNBC reported that the technology titan met with President Donald Trump.
Brooke Seawell, venture partner at New Enterprise Associates, sold about $24 million worth of Nvidia shares, according to an SEC filing. Seawell has been on the company’s board since 1997, according to the company.
Huang still holds more than 858 million shares of Nvidia, both directly and indirectly, in different partnerships and trusts.