Fund Manager Says Arm Holdings Beats Nvidia as Key AI Stock
1h ago|4 min readStandard
Fazen Markets Editorial Desk
Collective editorial team · methodology
artificial-intelligencesemiconductors
Fazen Markets Editorial Desk
Collective editorial team · methodology
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Portfolio manager Jonathan Cofsky argues that the most pivotal company enabling the artificial intelligence revolution is not Nvidia Corp. but Arm Holdings Plc. In an interview published on June 2, 2026, Cofsky detailed his view that while Nvidia’s GPUs are the current engine of AI processing, Arm’s fundamental chip architecture provides the indispensable foundation for the entire ecosystem. This perspective challenges the dominant market narrative that has propelled Nvidia's stock to a price of $224.36, a gain of 4.72% as of 12:18 UTC today, with shares trading in a range of $215.70 to $224.87.
The debate over critical AI infrastructure intensifies as the technology moves from hyperscale data centers to edge devices and personal computers. Nvidia has seen its valuation soar on the back of massive demand for its H100 and Blackwell GPUs, which train and run large language models. However, the scalability and energy efficiency demands of next-generation AI applications are shifting focus to the underlying processor designs that enable more widespread deployment.
Arm’s business model centers on licensing its energy-efficient instruction set architecture to hundreds of semiconductor companies, including Apple, Qualcomm, and Nvidia itself. This architecture dominates the mobile and embedded systems markets. The recent push to run AI models directly on smartphones, laptops, and IoT devices, rather than relying solely on cloud data centers, positions Arm’s technology as a potential bottleneck and high-margin beneficiary.
The last significant shift in computing architecture was the rise of x86 dominance by Intel and AMD in the PC and server markets, a position that has been eroding since Apple’s 2020 announcement to transition its Mac computers to its own Arm-based M-series chips. This transition demonstrated the performance-per-watt advantages of Arm designs in consumer hardware.
Nvidia’s market performance underscores its current leadership, with the stock climbing 4.72% to $224.36 in the session. The stock reached an intraday high of $224.87, reflecting strong bullish sentiment. This performance significantly outpaces the S&P 500’s average daily move. Nvidia's market capitalization has swelled to over $2.2 trillion, making it one of the most valuable companies globally.
In contrast, Arm Holdings, which had a standout IPO in September 2023, operates on a different financial model. Arm’s revenue is driven by licensing fees and royalties. For its fiscal fourth quarter, Arm reported royalty revenue of $514 million, a 37% year-over-year increase, highlighting the growing adoption of its newest v9 architecture, which commands higher royalty rates. The company’s licensing revenue for the same period was $354 million.
The following comparison illustrates the fundamental difference in their financial scales and models:
| Metric | Nvidia | Arm Holdings |
|---|---|---|
| Trailing P/E Ratio | ~45x | ~90x |
| Primary Revenue Source | GPU Hardware Sales | Architecture Licenses & Royalties |
| Q4 Revenue (Approx.) | $26 billion | $868 million |
Arm’s valuation multiples reflect high growth expectations for its licensing model as the total addressable market for AI chips expands.
Cofsky’s thesis implies that the AI value chain has a critical, high-margin choke point at the architectural level. If Arm’s designs become the standard for efficient AI inference on billions of devices, its royalty stream could become a predictable, high-growth annuity. This would benefit companies like Apple and Qualcomm, which design their own Arm-based chips, potentially at the expense of traditional x86 suppliers like Intel and AMD in certain segments.
The primary risk to this bullish Arm narrative is execution. While the architecture is pervasive, Arm must successfully enforce its v9 royalty rates and continue innovating to fend off open-source alternatives like RISC-V. RISC-V presents a long-term, existential threat as a free and open architecture, though it currently lacks Arm’s mature software ecosystem.
Market positioning shows heavy institutional ownership of Nvidia, but hedge funds are increasingly building strategic long positions in Arm as a play on the democratization of AI processing. Flow data indicates growing options activity in Arm, targeting further upside based on royalty revenue beats in upcoming quarters. For more on semiconductor market dynamics, see our analysis on `https://fazen.markets/en`.
Arm’s next earnings report, scheduled for late July 2026, will be a key catalyst. Investors will scrutinize the penetration rate of its v9 architecture, with royalty revenue growth being the most critical metric. Any announcement of a major new licensing deal with a cloud provider or automotive company could serve as a significant positive catalyst.
For Nvidia, the next major event is the Blackwell GPU ramp-up through the second half of 2026. Supply chain data on wafer orders and shipments will indicate whether demand is meeting extraordinarily high expectations. Technical levels to watch for NVDA include the psychological $200 support level and the recent high near $225 as resistance.
The broader semiconductor sector will be influenced by the U.S. Federal Reserve’s policy meeting on June 18. Interest rate expectations impact the valuation of long-duration growth stocks. A sustained move in the 10-year Treasury yield above 4.5% could pressure high-multiple tech stocks, while a decline toward 4.0% would likely provide a tailwind.
Arm generates revenue through upfront licensing fees paid by companies to access its chip blueprints and through ongoing royalties, typically a small percentage of the selling price of every chip sold that uses its architecture. The more AI-capable chips—from smartphones to data center processors—that are built on Arm designs, the greater its royalty revenue. Its newer v9 architecture commands higher royalty rates, directly benefiting from the AI boom as chipmakers adopt it for advanced features.
Nvidia’s GPUs are specialized hardware designed for massive parallel processing, making them ideal for the intense mathematical computations required to train AI models. Arm’s CPU designs are general-purpose processors focused on energy efficiency, handling the broader tasks of a device’s operating system and applications. The distinction is blurring as Arm designs incorporate AI acceleration blocks and Nvidia integrates Arm CPU cores into its chips, but their primary functions and business models remain distinct.
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