Nvidia's Data Center Business Grows in Fourth Quarter

We are raising our fair value estimate for the firm.

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NVIDIA Corp
(NVDA)

Nvidia NVDA reported fourth-quarter results ahead of management’s guidance, as the firm’s GPUs for artificial intelligence workloads enjoyed strong demand from major hyperscale and consumer Internet customers. We were pleased to see inventories return to a more normalized level following the cryptocurrency-related headwinds that plagued the firm in early 2019. Data center revenue grew considerably, as customers leverage both Nvidia’s training and inference GPUs key AI applications such as natural language understanding, conversational AI, and deep recommendation engines. After rolling our valuation model forward and incorporating slightly stronger growth in data center sales for the current year, we are raising our fair value estimate to $160 per share from $145. Nevertheless, we view shares as overvalued as we think current levels imply Nvidia is the sole beneficiary of the burgeoning AI and self-driving trends.

Fourth-quarter sales grew 3% sequentially and 41% year over year to $3.1 billion. The sharp year-over-year spike can be attributed to an artificially deflated fourth quarter in fiscal 2019 (calendar 2018) due to the massive decline in gaming GPU sales during that period stemming from a decline in demand in GPUs for cryptocurrency mining. Gaming sales fell 10% sequentially to $1.5 billion due to seasonally lower notebook GPUs and Nintendo Switch chip sales, partially offset by growth in desktop GPUs. While we do not anticipate major share loss to AMD, we do expect a more competitive environment that should pressure Nvidia’s ASPs going forward. Data center sales were $968 million, up 43% year over year and 33% sequentially. Both T4 inference and V100 training GPUs were shipped in record volumes, while T4 shipments were up 4 times year over year due to public cloud deployments. While major cloud players have all adopted the T4 in their data centers, we continue to expect a fragmented inference chip market, with FPGAs, ASICs, and even CPUs being prominent.

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About the Author

Abhinav Davuluri

Strategist
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Abhinav Davuluri, CFA, is a strategist for Morningstar Research Services LLC, a wholly owned subsidiary of Morningstar, Inc. He covers microprocessors, wafer manufacturing equipment, and other companies in the semiconductor space.

Before joining Morningstar in 2015, Davuluri spent two years as a process engineer for Intel.

Davuluri holds a bachelor’s degree in chemical engineering from the University of Michigan. He also holds the Chartered Financial Analyst® designation.

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