Following Nvidia’s launch of its new artificial intelligence (AI) chip “Blackwell” on the morning of Mar 19, analysts from DBS Group Research and Morningstar Equity Research have raised their fair value estimates for the stock to US$1,006.40 ($1350.32) and US$910 respectively.
Nvidia’s CEO Jensen Huang introduced the company’s latest AI graphics processor at its GTC conference in San Jose, California. The event, touted by some analysts as the “AI Woodstock”, showcased the efforts of the company’s wide range of partners in areas such as robotics and automotive, among many others.
Morningstar’s analyst Brian Colello says that he does not foresee these partners slowing their investments anytime soon, which supports his healthy growth estimates for Nvidia in the years ahead.
The analyst has taken a fresh look at his model assumptions and is more optimistic about future industry wide capital expenditure (capex) on AI graphics processing units (GPUs) in the decade ahead from both cloud computing vendors and enterprises.
Looking at cloud capex, Colello believes that much of the rise in Nvidia’s share price in 2024 — up 77% ytd versus 7% for the Morningstar US Market Index — and future earnings growth stems from hyperscale and enterprise capex.
These firms expect to spend incrementally more capex on AI GPUs in 2024, while also shifting the mix of “maintenance” capex away from traditional networking and server gear toward AI GPUs, the analyst notes.
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“Nvidia has captured a much larger piece of the data centre capex pie in recent quarters, and we anticipate that this mix shift will be the new normal for IT departments. Along these lines, we remain impressed with Nvidia’s ability to elbow into additional hardware, software, and networking products and platforms,” he adds.
Hyperscaler capex should be meaningfully higher in 2024, with Nvidia receiving a windfall from such spending, and we now anticipate even higher industry wide data centre capex as more and more businesses invest in AI, says Colello.
“We reiterate our very high Morningstar uncertainty rating as we concede that these capex plans, AI workloads, and competitive dynamics are changing rapidly. We now view Nvidia’s shares as fairly valued,” he adds.
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That said, the analyst notes that AMD recently lifted its total addressable market, or TAM, estimates for the AI accelerator market (including memory chips) in 2027 to US$400 billion from US$150 billion.
Even though he is more optimistic about spending on AI accelerators in the years ahead, the analyst still doesn’t foresee Nvidia and its peers reaching this US$400 billion threshold as soon as 2027.
“If AMD’s forecast is accurate and Nvidia can retain its AI GPU market leadership, then our revenue assumptions for the company might turn out to be conservative,” he says.
Despite increasing his fair value estimates, Colello keeps competitive pressures in mind. Nvidia’s hefty operating margins are everyone else’s opportunity, he says, and every company in the AI ecosystem has incentive to be more efficient in AI spending and find alternative sources to Nvidia—either in-house or among other vendors.
However, he still thinks that Nvidia will retain the bulk of the AI workload business — certainly in AI training and perhaps a hefty piece of AI inference workloads as well.
At Nvidia’s GTC conference, Colello says the launch of the Nvidia Inference Microservices (NIM) was of intrigue. This allows businesses to bring custom application and pre-trained AI models into production environments, which should aid these firms in bringing new AI products to market, says the analyst.
“We view Nvidia as dominant in AI training workloads, but we think that one of the highlights of the firm’s blowout quarter in late February was its disclosure that 40% of its deployed GPUs are being used for AI inference,” he says.
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Overall, Nvidia’s hardware products announced at GTC appear impressive and will likely remain best-of-breed in the industry, says Colello.
Nvidia’s latest GPU, Blackwell, is built by Taiwan Semiconductor Manufacturing on its 4NP process and includes 208 billion transistors, double the size of its prior-generation Hopper H100 GPU. The Grace Blackwell Superchip, GB200, connects two B200 Blackwell GPUs with an Arm-based Grace CPU.
“We’re still keeping an eye on Nvidia’s attach rate with Grace, as it may allow Nvidia to capture an even greater piece of the GPU server pie away from x86 CPUs from Intel or AMD,” the analyst says.
As such, Colello’s new fair value estimate implies a fiscal 2025 (ended January 2025) price/adjusted earnings multiple of 35x and fiscal 2026 multiple of 26x. His fiscal 2025 revenue estimates of US$116 billion in total and US$101 billion in data centre revenue for Nvidia are unchanged.
However, he lifted his longer-term data centre estimate for fiscal 2026 to US$135 billion from US$125 billion, and fiscal 2028 estimate to US$184 billion from US$141 billion, again driven by revised estimates for a higher TAM based on greater industry wide data centre capex spending.
Likewise, DBS says that Nvidia’s latest chip unveiling is “no surprise” as it looks to extend its AI-chip dominance.
The latest unveiled AI-chips attest to NVIDIA’s relentless pursuit towards cutting-edge technologies to extend its market-leading position in the AI chips space, says DBS analysts.
Data centre segment remains key to NVIDIA’s outperformance, which benefits from the robust demand for data centre AI-chips that is showing no signs of letting up, they add.
Even after a stellar FY2024 run, consensus expects data centre revenue, which accounts for about 87% of total revenue, to double to 101% y-o-y in FY2025, far exceeding the 10% growth in revenue growth for the company excluding data centre, say the analysts.
“We maintain our positive stance on Nvidia, as we see the data centre as the key beneficiary of the ongoing AI-boom. Maintain buy with revised higher target price of US$1006.40,” they add.
Shares in Nvidia are trading US$6.18 higher or 0.70% up at US$884.55.
