CNBC's Kristina Partsinevelos reports on Qualcomm's announcement of AI chips.

The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

Qualcomm has announced its entry into the data center AI chip market, targeting AI inference rather than training, which has been dominated by companies like NVIDIA. The new chips, set to launch in 2026, will be used by Saudi-backed startup Humane, with Qualcomm aiming to capture a portion of the growing multi-trillion dollar data center market.

The company's new server systems are based on its hexagon neural processing units, offering high memory capacity per card, which Qualcomm claims surpasses current offerings from NVIDIA and AMD. While only one customer has been named and no pricing details have been provided, Qualcomm is positioning its products as more power-efficient alternatives. The company faces competition from established players such as NVIDIA, AMD, and Google, which already have significant experience and market presence in AI inference.

Qualcomm announces new data center AI chips to target AI inference

Well, Qualcomm just announced it's taking on NVIDIA in AI chips, a massive pivot for a company that built its empire on smartphones. So they're launching new data center AI chips starting in 2026. And they also just announced their first major customer that would be Saudi backed AI startup Humane, targeting roughly 200 megawatts of capacity starting in 2026. So they're not essentially going after AI training. That's the market that made NVIDIA worth over $4 trillion. Qualcomm is targeting inference that's running AI models, not necessarily building them. So every time you use chat GPT or generate an AI image, that's inference. So training builds the models. Inference uses them billions of times a day. Qualcomm thinks the market is going to be enormous, nearly six point trillion, almost $7 trillion in data center spending is expected through 2030, according to McKinsey. And so just capturing about five to 10%, maybe just even 5% of that market would transform Qualcomm's business. Their products are complete server systems based on their hexagon NPUs. So that'd be neural processing unit chips already used in billions of smartphones around the world. One key advantage, and this is where it gets a little technical, it's 768 gigabytes of memory per card. They're saying that's more than what NVIDIA and AMD offer in this particular rack type setting. That matters, though, for running larger AI models. And so this is where Qualcomm hopes to compete. They'll sell these complete systems that you're seeing on your screen right now for, or also individual components. Qualcomm says even NVIDIA or AMD could become customers for some of their parts. But the timing really matters because, for example, OpenAI recently announced it's buying chips from AMD, showing big AI companies want alternatives to NVIDIA, especially within the inference market. But Qualcomm only named one customer so far. There's no pricing details. They're launching in 2026, which is years behind NVIDIA's dominance. But there's no taking away from the fact that this is a big new market for Qualcomm, guys. Yeah. And I mean, as you point out, Christina, no shortage of potential competitors, obviously AMD and NVIDIA, but others as well. And sometimes I don't think we talk enough about the fact that Alphabet, I mean, their TPU is for inference as well, right? Right. And gives them potentially a leg up to a certain extent. This is kind of a different subject, but on a cost per token basis in terms of what it costs them. And a lot of this goes back to that, I guess, for the hyperscalers. What is your, you know, what's the cost per token going to be? I don't know where this thing's going to get priced and what it's going to be able to do, but that will become important. Yeah. Normally in the chip world, they refer to it as total cost of ownership, TCO. And so Qualcomm didn't provide specific details. A lot of companies, how they benchmark it is different. They're saying that the total cost of ownership will be cheaper because of the power efficiency of said chips, because these aren't GPUs that are using a lot more power. The NPUs and more custom made chips tend to use a lot less. So that's going to be their selling point going forward. I'm sure in the coming months they'll reveal some more data around that. But to your point, Google really stands out. Even Jensen Wong from Nvidia has spoken many times about just how advanced Google has become in the TPU market. And just they've been here for a long time. This isn't a company that just made a chip, you know, five years ago. So that's another company to look out for, no doubt.

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Qualcomm announces new data center AI chips to target AI inference

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