Data Center And Tegra Processor Revenue Growth To Drive Nvidia’s Q4 Results

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Leading GPU maker, Nvidia (NYSE:NVDA) is set to report its Q4 2017 earnings on February 9th. In the previous quarter, the company posted revenue growth and margin growth of 53% and 280 basis points, respectively. Since then, Nvidia’s stock price has increased by more than 75%. The company has likely built on its growth momentum in this quarter as well. Though we shouldn’t expect any significant sequential growth in Nvidia’s key metrics in Q4, its growth has likely been strong on a year over year basis. In the table below, we can note the key metrics as expected for the company on Thursday:

Screen Shot 2017-02-08 at 4.25.27 PM

Source: Sec-filings

The company’s business model, based on driving GPU compute platforms into highly targeted markets, is clearly paying off. This is enabling Nvidia to extend its leadership across its segments. The company’s growth in the quarter has likely been driven by the following factors:

  • Strong Tegra processor revenues: In 2016, Nvidia announced that its Tegra processor will power Nintendo’s upcoming game console, the Switch. Landing this socket was a notable win for Nvidia, given that the company had failed to gain a spot for its Tegra processor in any leading gaming console until now. It should be noted that the Nintendo Switch is expected to hit the market by March. Nvidia has likely witnessed strong demand for its Tegra processors from Nintendo in Q3, as the latter is likely building up its inventory to prepare for the market launch of the Switch in March. Moveover, taken with the strong momentum of the company’s DRIVE PX 2 platform with autonomous car makers, it demonstrates that Nvidia’s strategy for its Tegra processor business seems to be successfully evolving since the company exited its efforts in the smartphones in 2015.
  • Healthy Growth In Data-center Revenues: Nvidia is witnessing an exceptional demand from cloud-based service providers. Major cloud-based service providers such as Amazon Web Services, Microsoft Azure and Alibaba Cloud are deploying Nvidia’s GPUs as coprocessors in their data centers to equip them with Artificial Intelligence (AI), data analytics and parallel computing. The company is expanding its deep learning platform beyond training to speed up AI inferencing production workloads in hyper-scale data centers.
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