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Home.forex news reportHow Far Can Nvidia Stock Climb After a Blowout Q4?

How Far Can Nvidia Stock Climb After a Blowout Q4?

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Nvidia (NVDA) delivered an exceptionally strong fourth quarter, beating expectations on both revenue and profit. Top-line growth accelerated from prior quarters, and earnings surged as demand for its artificial intelligence (AI) chips continued to expand across multiple markets.

Nvidia’s revenue growth is being driven primarily by its data center segment. Demand remains robust across a broad customer base that includes hyperscalers, major cloud service providers, AI model developers, large enterprises, and even national governments building sovereign AI infrastructure.

A key catalyst has been Nvidia’s next-generation Blackwell architecture, which is witnessing strong adoption. Further, management guided for continued sequential revenue growth throughout calendar 2026. That outlook signals that demand isn’t slowing. Importantly, AI infrastructure investment from large cloud providers and hyperscalers, which together account for over half of its data center revenue, has increased materially, indicating strong growth ahead.

Nvidia’s stronger-than-expected Q4 performance against elevated expectations, diversified demand, increasing AI infrastructure spending, and upbeat forward guidance strengthens its investment case and indicates further upside in the stock.

www.barchart.com
www.barchart.com

Nvidia is set to deliver solid growth ahead and offers strong visibility into future revenue, driven largely by continued demand for AI infrastructure. In the fourth quarter, Nvidia generated $68 billion in total revenue, a 73% increase from the same period last year. Growth also accelerated from the prior quarter, with the company adding $11 billion in incremental data center revenue sequentially.

The data center segment remains the core engine. Fourth-quarter data center revenue reached $62 billion, up 75% year-over-year (YoY) and 22% sequentially. Demand has been especially strong for Nvidia’s Blackwell architecture and the newer Blackwell Ultra systems, which are designed for large-scale AI training and inference workloads. As more companies deploy AI models into real-world applications, the need for inference computing power is rising alongside traditional training demand.



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