As you might expect, the company touts some impressive performance specs for these new TPUs compared to the previous generations: up to 3x faster AI model training, 80% better performance per dollar, and the ability to get 1 million+ TPUs to work together in a single cluster. The upshot should be a lot more compute for a lot less energy — and cost to customers — than previous versions. It calls these chips TPUs, not GPUs, because its custom low-power chips were originally named Tensor.

But Google’s chips are not a full frontal assault on Nvidia’s future, at least not yet. Like the other giant cloud providers, including Microsoft and Amazon, Google is using these chips to supplement the Nvidia-based systems it offers in its infrastructure. It is not flat-out replacing Nvidia. In fact, Google promises its cloud will have Nvidia’s latest chip, Vera Rubin, available later this year.

One day the hyperscalers building their own AI chips (which includes Amazon, Microsoft, and Google) may grow to need Nvidia less, as enterprises move their AI needs to their clouds and port their apps to these chips.

Still, as things stand today, it’s not profitable to bet against Nvidia. As notable chip market analyst Patrick Moorhead jokingly posted on X, he had predicted that Google’s TPU could be bad news for Nvidia (and Intel) back in 2016 when the search giant launched its first one. Nvidia is now a nearly $5 trillion market cap company, meaning that prediction didn’t exactly hold up to the test of time.