Bank of America sees Nvidia’s next $20 billion business
Nvidia (NVDA) stock investors have been fed a familiar playbook. More robust accelerators, higher rack prices, and another wave of hyperscaler spending were expected to propel Nvidia stock's valuation to even more stratospheric levels. Bank of America's latest semiconductor outlook, shared with me, ...
Overview
Nvidia (NVDA) stock investors have been fed a familiar playbook.
More robust accelerators, higher rack prices, and another wave of hyperscaler spending were expected to propel Nvidia stock's valuation to even more stratospheric levels.
Bank of America's latest semiconductor outlook, shared with me, offers an interesting twist on that view.
The bank's analysts, led by veteran tech analyst Vivek Arya, argue that a rapidly emerging AI workload is driving demand in an area investors have largely overlooked.
It sits beside Nvidia’s relentless GPU franchise but opens the door for a new revenue pool as companies move from training chatbots to deploying autonomous agents at scale.
The note also comes at a time when Nvidia stock investors are looking for new evidence to keep the stock's remarkable rally alive and propel it into a meaningful next leg higher.
At the time of writing, Seeking Alpha data show Nvidia in the red over the past month, despite posting a 9% gain year to date.
Despite being relatively strong, those gains pale in comparison with what Nvidia delivered in 2024 and 2025, when the stock returned 171% and 39%, respectively, according to SlickCharts.
BofA's note, however, raises the question of whether investors are still valuing Nvidia as merely a chip leader as it becomes something much larger.
Bank of America sees a $20 billion opening
Nvidia’s (NVDA) primary AI bottleneck has predominantly been GPUs.
However, as companies move from chatbots to agentic AI, the pressures are shifting toward CPUs instead.
For context, according to Nvidia’s latest CFO commentary on Q1 sales, Data Center compute revenue, led by its Blackwell GPUs, reached $60.4 billion, accounting for roughly 74% of the company’s $81.6 billion in quarterly sales.
Though that remains critical and will continue to be so for Nvidia, BofA has identified a massive new opportunity for Nvidia's Vera CPU.
BofA says Nvidia expects about $20 billion in Vera CPU sales during the second half of fiscal 2027. Roughly 50% of that could come from CPUs supporting GPU systems, while the rest may come from standalone CPU racks built for agentic AI and reinforcement-learning workloads.
The scale is amazing.
Nvidia might ship 4 million to 5 million Vera CPUs in the first two quarters after launch, compared with 2.5 million Grace CPUs shipped to date. Additionally, Vera could carry an average selling price of roughly $4,000 to $5,000 per chip.
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Zooming out, the larger opportunity is far more striking.
Details
According to Reuters, Nvidia frames the agentic-AI CPU market at about $200 billion, and that estimate excludes traditional general-purpose server workloads.
To understand the role of CPUs in agentic AI, think of them like project managers.
They coordinate tools, memory, databases, operating systems, and step-by-step decisions, while GPUs handle the complicated AI calculations.
For investors, that points to a provocative possibility: CPU unit demand may eventually exceed GPU demand as processors appear in both accelerator racks and separate agentic AI systems.
Artur Widak/NurPhoto via Getty Images
Nvidia wants to own more of every AI system
Nvidia is looking to cast a much wider net across the AI ecosystem by capturing a larger share of the infrastructure surrounding its GPUs.
BofA estimates Nvidia’s content per gigawatt could rise from roughly $40 billion with Blackwell Ultra to $60 billion to $80 billion with Rubin and Rubin Ultra, and potentially approach $100 billion with Feynman.
Nvidia is packing CPUs, networking, storage, interconnects, and additional racks around its core accelerators, expanding its larger revenue opportunity in the process.
That also opens the door for more competition, though.
AMD is pushing higher-core-count CPUs and rack-scale systems. Intel is defending its server franchise while betting on foundry progress. Arm-based designs are gaining market share, while Amazon, Google, and Microsoft continue to develop custom processors optimized for their own workloads.
Though Nvidia’s full-stack advantage remains elusive, there are pricing pressures, market share fluctuations, and bigger customer bargaining power, which are major issues. Hyperscalers also have an incentive to limit their dependence on one supplier.
For Nvidia stock investors, that adds a new layer to its already illustrious growth story.
For instance, in late May, HSBC raised its Nvidia price target to $325 from $295 and said that the established GPU roadmap may no longer be sufficient on its own to trigger a major re-rating, Investing.com noted. But new markets, such as agentic-AI server CPUs, could become the next valuation narrative.
Bank of America says Nvidia still looks unusually cheap
Amid the recent sell-off, BofA analysts are bullish on Nvidia stock, maintaining a buy rating and a $350 price target while naming it a top AI pick.
BofA estimates the shares trade at nearly 16 times calendar 2027 earnings, despite Nvidia’s growing reach across GPUs, CPUs, networking, storage, and entire AI systems.
Additionally, the bank also values Nvidia at nearly 0.4 times its price-to-earnings-growth ratio, behind the Magnificent 7 average of approximately 1.9 times.
In essence, the argument is that investors are still underestimating the durability of Nvidia’s tremendous earnings growth.
However, the risks are obvious, too. Despite being attractively valued according to BofA analysts, Nvidia has little room to disappoint.
If we see any sluggishness in AI spending, competitive pressure, or weaker system adoption, the valuation case could quickly be challenged.
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Source
Originally published at www.thestreet.com.
