$NVIDIA(NVDA)$ CNBC reported that Nvidia's Groq 3 LPX rack is in full production and set to be deployed alongside Vera CPUs and Rubin GPUs at neocloud provider Nebius later this year, according to Nvidia senior director Dion Harris.
The rack represents the commercialization of technology from Nvidia's $20 billion acquisition of Groq's assets in December, its largest deal on record. Each liquid-cooled rack packs 256 Groq chips. Nvidia says the rack can deliver 3,400 tokens per second, citing a benchmark from Artificial Analysis. Groq's chips are manufactured by Samsung, unlike Nvidia's own GPUs, which are made by Taiwan Semiconductor Manufacturing Co.
On the financial side, the $20 billion Groq deal looks manageable relative to the strategic capabilities it adds. Bernstein analyst Stacy Rasgon told CNBC that Nvidia is financially strong enough to absorb a deal of this size with little impact on its overall position. That leaves room to make large strategic investments and move into new AI chip technologies without seriously straining the balance sheet.
Groq's technology extends Nvidia's reach across the full AI compute stack rather than creating a rival product line. LPX handles low-latency inference while Nvidia's GPUs continue handling training and large-context processing. The rack can pair with Vera Rubin chips without customers changing their CUDA workflows, which deepens the software lock-in that has made Nvidia hard to displace.
Execution has been fast, and that matters in a market moving this quickly. Nvidia went from announcing the Groq purchase in December to full production and a named customer, Nebius, in eight months. It is a pace that shows Nvidia can absorb acquired technology and ship it rather than let it stall in integration.
Nvidia's inference speed now has a quantified edge over a key rival's approach. The Groq rack's 3,400 tokens per second compares with the 750 tokens per second OpenAI has promised for its Cerebras-powered "Ultrafast" mode. That gives Nvidia a benchmark it can point to as cloud providers shop for faster, more responsive AI inference.
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