Graphics chip giant Nvidia (NVDA) announced its Q3 earnings after the closing bell on Wednesday, beating analyst expectations for revenue but falling short of earnings per share.
Here are the key numbers from the report, compared to what Wall Street was looking for, as compiled by Bloomberg.
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Revenue: $5.93 billion versus $5.79 billion expected
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Custom WPA: $0.58 versus $0.70 expected
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Gaming Income: $1.57 billion versus $1.32 billion expected
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Data Center Revenue: $3.83 billion versus $3.7 billion expected
Nvidia’s fourth-quarter revenue forecast fell just short of Wall Street expectations, coming in at $6 billion. Analysts had expected $6.09 billion.
Shares of Nvidia rose about 2% after the report.
Data center revenue was up about 31% year-over-year in the quarter, but gaming revenue was down 51% year-over-year
Chip stocks have been hammered this year as consumer and business demand for electronics has ebbed after the explosive growth the industry saw during the pandemic. Consumers don’t need as many computers after buying them up during shutdowns, and companies already have enough machines for their remote and hybrid employees.
Nvidia cut back on chip production in the second quarter, with CEO Jensen Huang telling investors the company is working to realign inventory to match customer demand for chips.
Nvidia’s graphics chips were so sought after during the pandemic that they sold for hundreds of dollars more than their retail price. But as consumers return to their pre-pandemic lives, demand for potato chips has declined and prices have returned to normal levels.
Nvidia is also working to ensure it can still sell its high-end products in China. Nvidia began offering its new A800 chip in the country in the third quarter as a replacement for the A100 chip, which the US government said was too powerful to ship to China. The government fears that China will use the technology for military applications.
Ahead of Wednesday’s earnings, Nvidia announced a partnership with Microsoft (MSFT) to build one of the most powerful AI supercomputers in the world using Nvidia’s chips and Microsoft’s Azure infrastructure. The computer is designed to help train large-scale AI systems.
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