Name: Meta Will Deploy Millions of Nvidia Processors
Uploaded: 2026-02-19T21:31:22.000Z
Duration: 4 min 35 s
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Metta planning to deploy millions of Nvidia processors in the next few years.

A deal that could add billions of dollars to Nvidia's balance sheet.

Bloomberg Intelligence Global head of tech research Mandeep Singh joins us now.

Mandeep, first of all, I mean, does Nvidia need this?

It's up pretty sharply off the back of this.

I thought there was already like pretty robust demand for what Nvidia is selling.

And look, this is probably matters way of locking in that Nvidia supply.

So not only are they using the GPUs, but they are also talking about using Nvidia's C CPUs.

I mean, traditionally all These companies used x86 architecture and Intel CPUs along with the GPU cluster that Nvidia had.

But now, you know, with this deal, they're talking about using Nvidia CPUs.

The other thing for Nvidia here is Anthropic has had a very steep rise in the last few months.

Entropic models aren't trained on Nvidia GPUs.

So from that perspective, you have a company that's doing really well on the model side that is not trained on Nvidia GPUs.

And so from that perspective, I think for both of them it's important that you know, Metta comes up with a model that is really good in terms of being a frontier model like Anthropics that is trained on Nvidia's latest cluster and obviously matter needs to lock in the supply.

That's a good point too because also Gemini, I mean of course they're yeah, using Google's.

I mean in all of this, can you will other companies look at the advances of Anthropic, of Gemini and start to rethink their supply chain because of that, that they don't want to be too reliant on Nvidia.

what Nvidia is saying is our latest Blackwell chips will give you 30x more token output than our prior architecture from Hopper.

So for the same unit of power you can have 30 times more output.

And so that throughput aspect of Nvidia chips is always there and that ties into how good the model will be that is trained on the latest chip.

So really what Nvidia needs is companies like OpenAI, like Metta training their models on Nvidia's chips and having somewhat of an advantage compared to the ones that are not trained on Nvidia.

Where do some of these other competitors stand?

I think AMD gets hit even with this tie up between Metta and Nvidia, where Nvidia is now supplying the CPUs.

Previously AMD or Intel was the supplier of CPUs to the data centers for Metta.

Now with Nvidia selling CPUs that could have an impact on AMD.

Are you surprising that a company like intel that has a government backing there haven't been more political forces?

Because this is what was talked about, right?

The US takes a stake and pushes companies to start using intel for things like CPUs.

Are you surprised that we haven't really seen that?

Well, intel still has the foundry capacity.

So the difference between an intel and AMD is intel owns its foundries, where it makes its chips.

I mean intel, it has a local foundry that all these chip makers could use.

But obviously the government role comes into play in terms of pushing these companies to start using Intel Foundry more and more.

So just the one other concern that we have to bring up, as we do with any of these conversations, is the circularity of deals.

The fact that Metta already makes up a nice chunky portion of Nvidia's revenue, presumably that just reinforces that you say it's a good thing for Nvidia.

But is there also kind of like a dark side to the silver lining?

I mean, look, all these companies have an ecosystem.

So that circularity also exists in, you know, Google investing in Anthropic and Anthropic using Google's chip.

Same thing with the Amazon Anthropic partnership.

And at the end of the day it is an ecosystem because you're optimizing on a certain chip vendor for your model training and your model inferencing and you can't have a generic architecture.

And that's why, you know, they are very keen to partner with the companies of meta scale.

You want to make sure they optimize on Nvidia chips as opposed to using someone else's.

You probably wish for a boring day that might be nice.