Nvidia’s licensing deal with AI chip startup Groq highlights how Big Tech is securing talent and technology in inference while avoiding full acquisitions and antitrust risk.
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| As AI shifts from training to inference, Nvidia’s deal with Groq underscores how licensing and talent grabs are redefining competition in the chip industry. Image: CH |
SAN FRANCISCO, United States — December 25, 2025:
Nvidia’s decision to license AI chip technology from startup Groq—while hiring away its chief executive and senior engineers—offers a revealing snapshot of how the artificial intelligence boom is reshaping dealmaking in Silicon Valley. Rather than pursuing a full acquisition, Nvidia has opted for a structure that delivers much of the strategic upside while sidestepping the regulatory scrutiny increasingly attached to Big Tech mergers.
The move comes as competition intensifies in inference, the stage where trained AI models generate responses for users. Nvidia remains dominant in training large models, but inference is emerging as a critical battleground, with rivals such as AMD and startups like Groq and Cerebras Systems offering alternative architectures. By securing a non-exclusive license to Groq’s technology, Nvidia gains exposure to a promising approach without formally removing a competitor from the market.
Groq’s rapid rise helps explain Nvidia’s interest. The company more than doubled its valuation to $6.9 billion from $2.8 billion in August last year after raising $750 million in a September funding round. Investors have been drawn to Groq’s focus on serving AI models efficiently at scale, a challenge that is becoming more urgent as chatbots and other AI services move from experimentation to widespread deployment.
Technologically, Groq differentiates itself by avoiding external high-bandwidth memory chips, which are in tight supply globally. Instead, it uses on-chip SRAM memory, reducing exposure to the industry’s memory crunch and enabling faster interactions with AI models. The trade-off is that this design limits the size of the models that can be served, making it best suited to certain inference workloads rather than the largest frontier models.
Cerebras Systems, Groq’s closest rival using a similar approach, underscores how competitive the space has become. Cerebras is reported to be planning an initial public offering as soon as next year, and both companies have secured sizable commercial deals in the Middle East. Their progress highlights how startups can still carve out niches even as Nvidia dominates much of the AI hardware ecosystem.
Talent acquisition is central to Nvidia’s strategy. Groq founder Jonathan Ross, a veteran of Google’s early AI chip efforts, along with Groq’s president and key engineers, are set to join Nvidia. The pattern mirrors recent moves across Big Tech, with Microsoft, Meta and Amazon all paying heavily for AI leadership and expertise through licensing arrangements or executive hires rather than outright takeovers.
These structures are drawing growing attention from regulators. Analysts note that while non-exclusive licenses preserve the formal appearance of competition, the loss of leadership and technical talent can leave startups effectively weakened. Still, none of the recent AI licensing-and-hiring deals has been unwound, suggesting companies believe the approach remains defensible.
Nvidia CEO Jensen Huang has publicly argued that the company will maintain its lead as AI markets shift from training to inference, devoting much of his largest keynote of 2025 to that message. The Groq deal suggests a more nuanced reality: even as Nvidia projects confidence, it is moving pragmatically to absorb promising technologies and people—without triggering the political and legal costs of buying entire companies outright.
In that sense, the agreement is less about Groq alone than about a broader transformation in how AI power is consolidated, one license and one executive hire at a time.