Groq raises $650M for its cloud service despite the Nvidia deal

Groq is raising $650 million from its existing investors to develop its cloud model inference service. The funding arrives exactly six months after an unusual deal with Nvidia, which paid investors $20 billion, hired several key engineers and licensed Groq's technology.

The Nvidia deal: not an acqui-hire, but something new

In December, Nvidia made an unusual move. Instead of buying Groq outright, it paid investors $20 billion in cash, a way to reward them for their investment. At the same time, Nvidia hired several senior engineers from Groq and licensed the company's hardware technology. The rest of the team stayed on at the startup.

This scenario usually kills a company. Losing the best people typically means the end of the project. But investors decided to keep funding Groq's cloud business. Evidently they saw value in it even without parts of the original team.

Why the cloud is worth the money

The market for cloud model inference is growing fast. Companies are looking for places where they can run large models cheaply and quickly. Over the years, Groq has built up experience and customers. Even weakened, the startup has kept a valuable asset: its infrastructure and know-how.

$650 million is enough to hire new top-level engineers, expand the cloud service and compete with Together AI and other players. That should last 2-3 years of independent development.

A new model for big companies

Groq's story shows a shifting strategy among players like Nvidia. Rather than absorbing startups whole, they now often prefer selective hiring and technology licensing. That gives them talent without the burden of integrating an entire company.

"This is a new way for corporations to work with innovation," is the

logic big AI companies are following in 2026.

For investors, it is a good deal: they get cash. For startups, it is a test: surviving takes iron will and the right business focus.

What this means

Groq is trying to prove that a cloud business can survive and grow even after losing part of its team. If it succeeds, it will signal to other startups that the right focus and a growing market can withstand staff upheaval. It also shows how valuable cloud model inference has become in the eyes of investors and large companies.