Nvidia (NVDA) is a semiconductor giant and artificial intelligence king. It makes GPUs, CPUs, AI inference accelerators, and networking solutions (which are becoming increasingly more important).
The company divides its revenue sources into five end markets: Data Center, Gaming, Professional Visualization, Automotive, OEM, and Other.
The stock is up approximately 15.3% year to date, at the time of writing, Friday afternoon, May 8, trading near $215 according to Yahoo Finance. Meanwhile, the SPDR S&P 500 index (SPY) is up 8.1% in the same period.
The latest good news moving the stock is Nvidia’s partnership with IREN Limited (IREN) announced on May 7.
Key facts about the partnership:
The companies intend to deploy up to 5 GW of Nvidia AI infrastructure across IREN’s global data center pipeline over time.
IREN issued to Nvidia a five-year right to purchase up to 30 million shares of ordinary stock, resulting in a right to invest up to $2.1 billion
The goal of this partnership is to ramp up deployment of large-scale AI factories by combining NVIDIA’s DSX AI factory architecture with IREN’s expertise across power, land, data centers, GPU deployment, and infrastructure operations.
“AI factories are becoming foundational infrastructure for the global economy,” stated Jensen Huang, founder and CEO of Nvidia, in the press release.
A big push for AI factories is not surprising, as more than 89% of Nvidia’s revenue comes from data centers. This is shown in the company’s FORM 10-K. In fiscal year 2026, data center revenue hit $193.7 billion, while the total revenue was $215.9 billion.
However, the whole AI factories strategy consists of offering more than plain AI hardware.
Nvidia’s key selling point for AI factories is sovereignty. Data ownership, privacy, and model fine-tuning are among the reasons any company or organization that can afford it would want a sovereign AI.
However, for full AI sovereignty, the customer needs access to a high-quality open model, and Nvidia solves this with its line of Nemotron AI models.
On April 28, Nvidia launched Nemotron 3 Nano Omni, an open, multimodal model with vision, speech, and language capabilities in a single system. The company said this allows AI agents to deliver faster, smarter responses with advanced reasoning across video, audio, image, and text.
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Companies already using the model include: Aible, Applied Scientific Intelligence, Eka Care, Foxconn, H Company, Palantir, and Pyler. Nvidia said that Dell Technologies, DocuSign, Infosys, K-Dense, Lila, Oracle, and Zefr are evaluating the model.
As Nvidia successfully improves its AI factory strategy, first-quarter earnings are getting closer, with the report set for release on May 20.
In a research note shared with me, Goldman Sachs analyst James Schneider and his team updated their opinion on Nvidia stock and earnings expectations.
Goldman Sachs raises Nvidia EPS estimates ahead of earnings
The team said they expect a beat-and-raise quarter based on positive industry supply-and-demand information. However, they noted that they believe that the bar for “stock outperformance is relatively high heading into the print”.
Analysts raised their EPS estimates by approximately 12% on average and noted that the updated calendar-year 2026 and 2027 estimates are 14% and 34% above the Wall Street consensus, respectively.
Schneider expects Nvidia to deliver an approximately $2 billion revenue beat in Q1 with revenue of $80 billion. He estimates Q2 revenue of $87.68 billion, which is 3% higher than the Wall Street consensus. His Q1 and Q2 EPS estimates (excluding stock-based compensation) are $1.86 and $2.05, which are 7% and 8% above the Wall Street consensus, respectively.
Analysts noted items on the earnings call that could move the stock:
The magnitude of upside to Nvidia’s $1 trillion datacenter guidance at GTC.
Potential upside from agentic AI to the server CPU business.
Competitive dynamics.
Gross margin outlook given rising input costs.
In a research note shared with me, Schneider reiterated a buy rating for Nvidia stock and the target price of $250, based on a 30x price-to-earnings ratio multiple applied to his normalized EPS estimate of $8.25.
For Nvidia’s stock multiple to be re-rated, analysts need to see evidence of improving profitability metrics at hyperscalers, the proliferation of agentic AI, and greater visibility into deployments with nontraditional customers.
Analysts noted key downside risks for Nvidia:
Slowdown in AI infrastructure spending,
Share erosion due to increased competitive intensity,
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