Thursday, March 12

Bank of America has stark message for Nvidia investors ahead of GTC


With Nvidia‘s flagship GPU Technology Conference (GTC) just days away, Bank of America is telling investors exactly what to watch and why the stock’s current valuation may not reflect what is coming.

Analyst Vivek Arya reaffirmed a buy rating on Nvidia (NVDA) with a $300 price target ahead of the March 16 GTC keynote from CEO Jensen Huang. The note flags three specific areas of focus that Arya believes could be the clearest signals of Nvidia’s trajectory through 2027 and 2028.

The timing matters. Nvidia shares are currently trading at what Arya describes as a historically depressed forward price-to-earnings multiple of 17x, a level he calls a trough following the Blackwell architecture’s massive $500 billion cumulative sales ramp.

The bank sees the GTC keynote as the catalyst that could begin closing that valuation gap.

Arya’s note is precise about what investors should focus on when Jensen Huang takes the stage on March 16. The three areas are not just product announcements. They are signals about how far ahead of competitors Nvidia’s roadmap actually extends.

  • Product roadmap through 2028: BofA expects Nvidia to outline its full pipeline from the current Vera Rubin platform through to Feynman GPUs in 2028, a three-generation visibility that Arya says locks in developer and enterprise commitments well ahead of rivals.

  • Co-designed inference portfolio: The bank anticipates announcements across a new range of customized products including CPX chips for inference prefill workloads and a Language Processing Unit, or LPU, for low-latency decode, potentially integrated inside Nvidia’s next-generation rack systems.

  • Proprietary optics in scale-up networks: BofA is watching for details on Nvidia’s next-generation 102.4T Spectrum-6 switch and the 115T Quantum-X with co-packaged optics, technology the bank says could become essential infrastructure in large-scale AI cluster deployments.

Much of the AI infrastructure conversation over the past two years has focused on training, the process of building large language models. Nvidia has dominated that market.

But the bank’s note signals that the next battleground is inference, the process of actually running those models at scale for end users.

More Nvidia:

BofA describes the new CPX and LPU products as “a new wave of co-designed and disaggregated AI infrastructure,” adding that these architectures could become increasingly important as AI workloads shift from training toward inference at scale.



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