Groq raises $650M to rebuild after Nvidia's $20B licensing deal took its founder and tech

AI chipmaker Groq confirms $650M raise, re-staffs after Nvidia's $20B not-acqui-hire deal

What does an AI company do after one of those not-acqui-hire deals, where a rival pays investors a hefty IP "licensing" fee while poaching its critical talent? For AI chipmaker Groq, the answer appears to be raise more money from investors -- who were said to have profited handsomely after a deal with Nvidia in December -- hire more talent, and pivot. On Monday, Groq announced a new $650 million funding round, confirming earlier reports. The raise comes roughly six months after Nvidia signed a non-exclusive licensing agreement for Groq's technology and hired away founder and CEO Jonathan Ross, president Sunny Madra, and other employees. Groq did not disclose its new valuation. It was last valued at $6.9 billion following a $750 million round in September. Ross, who came from Google, was known in the AI chip world for helping create Google's AI chip, the Tensor Processing Unit. He teamed up with another Google engineer, Doug Wightman, to launch Groq a decade ago. Wightman stayed on after the Nvidia deal and became CEO. Groq created a chip it called a language processing unit (LPU), used for inference, and sold it as part of a cloud service or an on-premises hardware cluster. With Nvidia now owning the IP for LPUs, the GPU giant announced its own hardware cluster, the Nvidia Groq 3 LPX inference hardware system, at its GTC event in March. In response, Groq has pivoted to its neocloud business, it said. That business had been run by Madra after Groq acquired his AI data analytics company Definitive Intelligence, in 2024. It has grown to 13 data centers across North America, Europe, the Middle East and APAC and is serving over five million developers and thousands of AI companies, processing trillions of tokens each week, the company says. Groq has also been hiring replacement execs. It added Alan Rice as COO, previously at xAI and Meta, after a career in the U.S. Navy. It also added an entrepreneurial duo, Sinclair Schuller, who joins as CTO, and Rakesh Malhotra as CPO. They previously worked together at Apprenda, an enterprise cloud software company founded by Schuller; they then co-founded Nuvalence, a software-engineering firm acquired by EY in 2024. Malhotra previously spent about a decade working on Microsoft's cloud products. Whether Groq can succeed after almost selling itself depends on how competitive its inference cloud can remain, now that the key hardware IP is shared with Nvidia. Certainly, it has a shot. Inference-related tech is an area experiencing tremendous demand (and VC investment). But it's also seeing increasing innovation and competition. Still, others seem to have survived these sorts of deals. Scale AI's CEO Jason Droege told Forbes that business has rebounded after Meta did a $14.3 billion not-acqui-hire about a year ago, and that the company is on track to do $1 billion in revenue. In the big money game of AI, anything seems possible.

Inference chip startup Groq raises $650M to grow its cloud platform

Inference chip startup Groq raises $650M to grow its cloud platform Seven months after inking a $20 billion chip licensing deal with Nvidia Corp., Groq Inc. today announced that it has raised $650 million in funding. Growth investment firm Disruptive and hedge fund Infinitum led the round. Groq has developed a chip design called the LPU that's specifically optimized for artificial intelligence inference workloads. In December, Nvidia agreed to license the technologies that underpin the processor. It also hired several key Groq employees, including its founding chief executive. The transaction produced the Nvidia Grok LPU 3, an inference processor that the chip giant debuted in March. It ships as part of a rack-size, liquid-cooled appliance called the LPQ. The system includes 32 trays that each host three Groq LPU 3 units, one central processing unit and network equipment. The accelerators in an inference cluster each include a quartz crystal called a clock that regulates processing speeds. Clocks also play an important role in coordinating the flow of data between chips. When accelerators' clocks move out of sync with each other, data traffic slows down, which negatively impacts AI model response times. The LPU 3 includes a feature that automatically fixes clock drift to avoid data traffic bottlenecks. According to Nvidia, the chip includes 92 lanes that can each move data to other processors at a speed of 112 gigabits per second. That translates to 2.5 terabits per second of bidirectional bandwidth. Accelerating the flow of data between chips is not the only way the LPU 3 speeds up inference workloads. The processor ships with 500 megabytes of onboard SRAM, a high-speed memory variety. SRAM is more performant than the off-chip RAM that other AI accelerators use to store data, which translates into faster inference. Groq operates an LPU-powered cloud platform that companies can use to run inference workloads. The company disclosed today that the platform is processing trillions of tokens per week for five million developers. Groq's cloud runs across 13 data centers spanning multiple continents. The company will use the proceeds from its funding round to grow its inference capacity with the goal of reaching 200 megawatts by 2027. According to Grow, some of the new processing power will be provided by the LPX, the liquid-cooled LPU 3 appliance that Nvidia debuted in March. Other cloud operators can theoretically build LPQ-powered inference services of their own. One way Groq could set itself apart from such potential rivals is by extending its platform with new services such as managed databases. Other AI-focused cloud providers, notably CoreWeave Holdings Inc., have also broadened their focus beyond infrastructure to higher-level services.