Nvidia & Meta – Safe for Now

Nvidia is not close to danger yet.  

• The worst-kept secret in tech is that Nvidia’s customers are all trying to reduce their dependence on Nvidia by building their own silicon, but it’s a slow process and with Nvidia’s product cadence, I don’t see it being in danger anytime soon.
• Meta is working with TSMC (and I presume Arm (see here)) to develop an in-house chip that it will use for all of its AI activities including training and inference of regular machine learning and generative AI.
• If successful, this would reduce or remove its dependence on Nvidia which given the size of Meta as a customer, would have significant and negative implications for Nvidia.
• For a large client of Nvidia to switch to its silicon is much easier than it is for a small company as the large company has its in-house captive market to drive the economics.
• It also does not have to worry about the dominance of Nvidia’s silicon development platform CUDA as it can make its systems vertically integrated and use its development tools.
• It does, however, have to make the platform as good as CUDA and its in-house silicon as economically viable as the latest and greatest from Nvidia.
• Hence, as always, the devil is in the details as:
  • First, product cadence: which I have long argued is one of Nvidia’s key differentiators.
  • Here, the latest product from Nvidia (currently Blackwell) is always at least one generation ahead of everyone else meaning that it will be the most cost-effective to operate even with Nvidia’s 70%+ gross margins.
  • This is the classic build vs. buy dilemma that any company has to weigh up and, at the moment, everyone else is far enough behind to make it more cost-effective to buy Nvidia.
  • Second, developers: where anyone who wants to have 3^rd party developers using their silicon has to solve the development platform problem.
  • Developers already know how to use CUDA and as it is the most mature in the industry, it remains a key control point and the reason why developers prefer Nvidia.
  • Consequently, with 3^rd parties, the CUDA problem needs to be overcome and given how far ahead it is, I think that unlikely that anyone will succeed in this generation.
  • However, RFM Research has long argued that the developer market will move from developing on silicon to developing on foundation models as models become increasingly commoditised.
  • The big foundation model providers are likely to ensure that their models can be trained optimally on Nvidia, their own silicon or anyone else as greater competition means purchasing the silicon for their data centres will cost less.
  • This is how the CUDA control point may weaken, and I think that it is not until then, that we will see any real pressure on Nvidia’s business model.
• Hence, I think that while Meta will have some success with its in-house silicon for its uses when it comes to 3^rd parties, it is going to be stuck with Nvidia for some time.
• RFM Research has also concluded that it will take a while for developers to shift towards foundation models meaning that for a few years yet, Nvidia’s market share is unlikely to change much.
• Consequently, Nvidia remains subject to the whims of demand which remains higher than it can deal with.
• Hence, revenues are likely to be a factor of how much capacity it has booked at TSMC for the coming 12 months as opposed to how much customers want to buy.
• The net result is that Nvidia’s short to medium visibility remains pretty good and so I do not expect any surprises in the next few earnings reports.
• However, this also means that the scope for a further large run-up in the share price is limited meaning that the share price is likely to remain in line with revenue and profit growth.
• Nvidia’s valuation is still relatively undemanding for the growth that it is likely to see in the next year or two, and so if I were forced to hold a direct AI investment, this would be it.
• However, I still prefer the adjacencies of AI inference at the edge of the network and nuclear power to solve the energy shortage both of which remain pretty cheap and underinvested.