Analysts home in on Nvidia’s inference market share following an earnings win. Here’s why
Artificial intelligence chipmaker Nvidia boosted its dividend, delivered a beat on earnings and revenue, and reported adjusted gross margins of 75% – but the stock still sank in extended trading after quarterly results released Wednesday. The “agentic” phase of the AI buildout has put the focus back on central processing units and more decentralized systems architecture, sending other chipmakers like Intel , Micron and AMD soaring in recent months while Nvidia performed a bit more modestly . NVDA AMD,INTC,MU 3M mountain Nvidia vs. Intel, AMD and Micron in the past three months Analysts wanted to know on Wednesday’s earnings call whether Nvidia will keep its edge as the playing field for chip demand broadens out. “With investors keenly focused on your market share in inference, how do you see Vera Rubin … impacting your share of the inference market?” CJ Muse, managing director at Cantor Fitzgerald, asked Nvidia CEO Jensen Huang. Vera Rubin is Nvidia’s upcoming AI system , slated to rollout later this year. Huang responded not once, not twice but five or six times that the company’s market share of inference – which refers to AI’s ability to answer questions and complete tasks for users and companies – was growing. “Our share of inference is growing very quickly,” he said. Nvidia is not the only kid on the block anymore when it comes to producing AI chips, which were synonymous with the graphics processing units that Nvidia specialized in. The newer “agentic” phase of AI – which refers to semi-autonomous bots that can be sent off to do tasks on their own, rather than more directly managed – requires a more distributed processing design that requires a greater number of more traditional CPUs than GPUs. While Nvidia is still undoubtedly the dominant player, the new infrastructure format is amping analyst interest in competition. It’s not clear yet if a specific kind of architecture is going to dominate the market or if chipmakers will increasingly specialize. Rival custom silicon products like Alphabet’s tensor processing units and Amazon’s Trainium chips, along with products from AMD and newcomer Cerebras , could potentially disrupt this market. However, Huang said that production bandwidth for Nvidia’s forthcoming Vera Rubin chip platform could be at capacity even before it ships later this year. “My sense is that we’ll be supply constrained throughout the entire life of Vera Rubin,” he said. Analysts are not seeing CPU or memory demand tapering any time soon. “Server CPU demand is strongly inflecting up, driving demand … for both conventional server as well as AI servers (CPU head nodes). Agentic AI is a key driver,” Nicolas Gaudois, analyst with UBS, wrote on Wednesday.
