Chip Designer Arm Files for its IPO, Eyes AI for Growth

U.K. chip designer Arm has filed its much anticipated initial public offering in New York, which reportedly could be the year’s largest.

It plans to list on the Nasdaq, under the ticker symbol ‘ARM.’ The IPO price and the number of shares to be offered are yet to be determined. Lead underwriters are Barclays, Goldman Sachs, J.P. Morgan and Mizuho.

Bloomberg is reporting that the IPO could value Cambridge-based Arm between $60 billion and $70 billion. That is between 50% to 75% higher than the $40 billion Nvidia offered in a now-scuttled acquisition deal.

The filing disclosed that Arm had $2.68 billion in revenue for the fiscal year ended March 31, slightly down from the prior year’s $2.7 billion but up 32% from 2021. Net income came to $524 million compared with $549 million in the previous year and $388 million in 2021.

The SoftBank-owned company designs chips that it licenses to other companies wishing to develop their own semiconductors for their own use or resale. It is known as the “Switzerland” of the chip industry and its designs have become a de facto industry standard for CPU processor technology, according to the U.S. Federal Trade Commission (FTC).

Arm’s chip designs are used in more than 99% of the world’s smartphones, according to its filing with the U.S. Securities and Exchange Commission (SEC).

Its chip designs also power anything from small sensors to supercomputers. According to its filing, CPUs that use its designs run the “vast majority of the world’s software” including those in smartphones, tablets, PCs, data centers, networking equipment, vehicles, smart watches, thermostats, drones and industrial robotics.

Arm said it is working with Alphabet, Cruise, Mercedes-Benz, Meta and Nvidia to deploy its technology to run AI workloads.

"In the emerging area of large language models, generative AI and autonomous driving, there will be a heightened emphasis on the low power acceleration of these algorithms,” Arm said in its IPO filing.

With AI requiring high compute capabilities, a typical approach is to increase the CPU speed and expand the number of processor cores per chip. But this also results in higher energy costs that may exceed thermal limits.

Arm’s chip designs are energy efficient, which is why they were suitable for mobile devices. It is betting that its designs will work for compute-intensive AI workloads in data centers because these chips can mitigate energy consumption.

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