Wall Street is focused on Nvidia (NVDA) graphics processing units (GPUs). The fastest growing story is at your side. Nvidia has quietly built a networking operation that generated nearly $15 billion last quarter, up from about $3 billion per quarter two years ago. Wall Street expects that figure to approach $17 billion when the company reports results on Wednesday. Computing still overshadows networking within Nvidia’s data center business. But networking has grown faster, nearly 200% year over year in the last quarter, compared to 77% for computing. That pace is slowing. Analysts expect networking growth of about 134% in the about-to-be-reported quarter, still ahead of computing at about 100%. Bloomberg, Yahoo Finance The change goes directly to one of the biggest questions hanging over Nvidia. Nowadays, everyone designs AI chips. Alphabet (GOOG, GOOGL), Amazon (AMZN), Microsoft (MSFT), Meta Platforms (META) and other hyperscalers are spending billions developing or launching custom processors that can handle some workloads without an Nvidia GPU. But those chips still have to communicate with each other. As AI data centers connect thousands of accelerators into giant computing systems, moving data between those processors becomes a challenge in itself. This has driven the trade of AI into networking, memory, storage and other infrastructure. Jessica Inskip, director of investor research at StockBrokers.com, described Nvidia’s strategy in Yahoo Finance’s initial offering on Tuesday as “investing in the bottlenecks that are AI infrastructure.” Networking is one of them. Nvidia is increasingly selling the pipelines that keep huge artificial intelligence systems running. Its Spectrum-X products connect servers over high-speed Ethernet, while InfiniBand and NVLink help move huge amounts of data between processors quickly enough to prevent expensive chips from sitting idle. More recently, Nvidia has pushed NVLink Fusion, which allows companies to connect their own custom processors to Nvidia’s broader system of high-speed connections, networking, power and cooling. Think of it as designing an entire server rack to function as one giant computer, rather than selling chips one by one. That changes the competitive equation. Nvidia stock has already been acting differently than much of the chip industry. NVDA has traded sideways for about the last two months while semiconductors fell into a bear market. · Yahoo Finance AlphaSpace Since semiconductor trading peaked around June 22, Nvidia stock has gone virtually nowhere, while the iShares Semiconductor ETF (SOXX) has fallen about 20%. As Tuesday’s chart of the day showed, Nvidia largely avoided the chip bear market that engulfed most of the group. Networking alone does not explain that resilience. But its rapid growth gives investors another reason to view Nvidia as something broader than a conventional semiconductor company. Wednesday night offers the next test. A networking figure close to $17 billion would keep the business at about a fifth of data center revenue. Investors will also be watching Jensen Huang’s comments on demand for networking, custom silicon and how much of the AI system Nvidia can capture beyond the GPU. Inskip described the broader ambition more simply. Nvidia, he said, is trying to become a “one-stop shop for everything” in AI. Jared Blikre is Yahoo Finance’s global markets and data editor. Follow him on X at @SPYJared or email him at jaredblikre@yahooinc.com. Click here for an in-depth analysis of the latest stock market news and events influencing stock prices. Read the latest financial and business news from Yahoo Finance.
