Key Takeaways
- Nvidia shares advanced 0.3% to $202.74 in premarket trading Tuesday, moving closer to its October record close of $207.
- Google is set to introduce its next-generation tensor processing units (TPUs) at the Google Cloud Next conference in Las Vegas, created in collaboration with Marvell Technology.
- The new TPU generation targets inference operations — where AI models process and answer user requests — instead of the training phase where Nvidia maintains market dominance.
- KeyBanc’s John Vinh reaffirmed his Overweight rating on Nvidia with a $275 price objective, highlighting the CUDA software platform as a significant competitive advantage.
- Google has secured major TPU customers including Meta with a multibillion-dollar agreement and Anthropic with access to as many as 1 million chips, though availability issues persist.
Nvidia continues its impressive trajectory. The semiconductor giant’s shares have surged 15% in the past month and are approaching their all-time peak. This upward trend persisted Tuesday morning despite Google’s impending announcement in the artificial intelligence chip sector.
Trading at $202.74 before the opening bell, Nvidia posted a 0.3% gain. The stock is closing in on its historic closing record of slightly above $207, established in October 2025.
The rally occurred as market participants anticipated quarterly financial results from leading technology firms. Investor sentiment regarding Nvidia’s growth prospects continues strengthening.
However, the landscape isn’t without challenges. Google plans to reveal its next-generation tensor processing units — TPUs — during the Google Cloud Next event in Las Vegas this week.
Focus on Inference Computing
Bloomberg reports indicate Google engineered its newest processors alongside Marvell Technology. These chips concentrate on AI inference: the operational phase where trained models generate responses to user inputs.
“The competitive landscape is transitioning toward inference,” Gartner’s Chirag Dekate explained to Bloomberg. Google Chief Scientist Jeff Dean reinforced this perspective, noting that specialized chips for training versus inference make strategic sense as artificial intelligence demand expands.
Google has invested in this direction for several years. The TPU initiative now includes Meta as a significant client — the social networking company inked a multibillion-dollar contract for TPU procurement through Google Cloud. Anthropic similarly extended its TPU capacity to potentially 1 million processors.
A structural advantage exists as well. Among prominent AI developers, none manufactures proprietary chips at a scale comparable to Google, creating tighter integration between model development teams and chip design engineers.
Google has simultaneously expanded TPU accessibility. PyTorch developers now have TPU support, and reports suggest the company is testing on-site TPU installations for corporate clients — representing a departure from its traditional cloud-exclusive approach.
CUDA’s Competitive Shield
Financial analysts remain confident in Nvidia’s position. KeyBanc’s John Vinh sustained his Overweight assessment on Nvidia Monday with a $275 target price, emphasizing that the CUDA software ecosystem establishes substantial obstacles for potential challengers.
“We perceive minimal competitive threats and anticipate Nvidia will maintain its dominance in one of the most rapidly expanding workloads across cloud and enterprise environments,” Vinh stated.
Nvidia CEO Jensen Huang has previously indicated his processors support capabilities “you can’t do with TPUs.” Significantly, Google continues deploying Nvidia GPUs alongside proprietary TPUs for artificial intelligence initiatives.
Nvidia’s forthcoming Vera Rubin platform is projected to remain the most sophisticated AI hardware available upon release.
Availability constraints may also impede Google’s objectives. An anonymous startup leader informed Bloomberg that TPU scarcity presented genuine difficulties, with restricted chip access beyond what Google allocated to “the more elite teams.”
