On December 24, 2025, a Christmas Eve headline jolted the AI hardware world: CNBC reported that Nvidia had agreed to buy AI chip startup Groq for about $20 billion in cash, a move that would rank among Nvidia’s biggest strategic bets in the AI era. [1]
But as the story raced across markets and social media, Groq published its own update: not an acquisition announcement, but a non-exclusive licensing agreement with Nvidia focused on Groq’s AI inference technology. In the same statement, Groq said its founder Jonathan Ross, Groq President Sunny Madra, and other team members will join Nvidia—while Groq continues operating as an independent company, with Simon Edwards stepping in as CEO and GroqCloud continuing without interruption. [2]
That contrast—a reported $20B takeover versus a confirmed licensing-and-talent move—is now the core of what makes the Groq-Nvidia news so consequential: it underscores how fierce the race has become to dominate the next phase of AI computing, where inference (running models in real time) is increasingly viewed as the battleground after the training boom. [3]
What happened on Dec. 24: report first, then a clarification-style announcement
Here’s what is clearly established from Dec. 24 reporting and statements:
- CNBC reported Nvidia was “buying” Groq for about $20 billion in cash and described it as Nvidia’s biggest deal. [4]
- Reuters later reported Nvidia had agreed to license Groq’s chip technology and hire away key executives, citing Groq’s blog post and noting a person close to Nvidia confirmed the licensing agreement. [5]
- Groq’s own newsroom post framed the deal as a non-exclusive inference technology licensing agreement—and emphasized continuity: Groq stays independent, GroqCloud keeps running, and leadership transitions to Simon Edwards. [6]
- Other market coverage described the earlier acquisition framing as an overstatement, pointing readers back to Groq’s post as the factual description of the arrangement. [7]
The net effect: whatever Nvidia and Groq are doing together is significant—especially because it includes the movement of core leadership and engineers—but the only primary-source announcement on Dec. 24 describes licensing, not a purchase price or a full takeover. [8]
Why Nvidia cares: inference is where the AI chip fight is headed
For most of the generative AI boom, Nvidia has been synonymous with the “training stack”—the expensive phase where giant models learn patterns from massive datasets. That dominance is why Nvidia became the default supplier for many AI labs and cloud providers.
But inference is different.
Inference is the moment of truth: when a trained AI model answers your question, summarizes a document, generates code, or powers an enterprise chatbot at scale. Those workloads are continuous, latency-sensitive, and cost-sensitive. And Reuters noted Nvidia faces much more competition in inference—from traditional rivals like AMD to specialized startups like Groq and Cerebras Systems. [9]
A licensing agreement that pulls Groq’s inference know-how—and key builders—closer to Nvidia is therefore easy to understand strategically: it’s a way to strengthen Nvidia’s position as the market shifts from “how models are trained” to “how AI is actually served to users.” [10]
Why Groq matters: the “LPU” approach and the speed-to-serve problem
Groq has built its brand around a chip architecture designed specifically for fast AI inference. Instead of relying on the same approaches used by many GPU-based systems, Groq promotes what it calls an LPU (language processing unit) built to prioritize low-latency execution.
In industry coverage, Groq has claimed its approach can run large language models dramatically faster and with better energy efficiency than GPUs—claims that helped it stand out in a market crowded with “Nvidia alternatives.” [11]
Reuters also highlighted one of Groq’s defining technical bets: it is among a set of upstarts that avoid external high-bandwidth memory (HBM)—a scarce, high-demand component in the AI supply chain—by leaning on on-chip SRAM memory. Reuters described this as a way to speed up interactions with chatbots and AI models, while also limiting the model sizes that can be served using that approach. [12]
That tradeoff—faster responses versus constraints on model size and memory capacity—is exactly the sort of engineering tension that matters when AI moves from demos to global-scale products. And it’s why Groq’s technology, even if merely licensed, can be strategically valuable to Nvidia. [13]
The executive shift is a major signal: Jonathan Ross heads to Nvidia
One of the most concrete and consequential facts in the Dec. 24 story isn’t the rumored price tag—it’s the people.
Groq said Jonathan Ross (founder) and Sunny Madra (president) will join Nvidia, along with other team members, to help advance and scale the licensed technology. [14]
Reuters identified Ross as a veteran of Alphabet’s Google who helped start Google’s AI chip program, adding more context to why his move matters for Nvidia’s competitive posture in inference. [15]
From a business perspective, this is the hallmark of a modern AI-era “deal”: not always a clean acquisition, but a structure that can combine technology rights + talent migration + ongoing independent operations.
Groq is explicitly saying it continues independently and that its cloud business continues. That points to a relationship that is closer than a typical partnership, but not framed as a standard acquisition in Groq’s own words. [16]
Groq’s valuation context: from $2.8B to $6.9B, and the $20B question
Groq is not a tiny lab project. Reuters reported that Groq more than doubled its valuation to $6.9 billion, up from $2.8 billion in August of the prior year, after a $750 million funding round in September. [17]
That valuation trail is one reason the reported $20 billion figure drew attention: it would imply a massive jump in value in a short period—if the reported acquisition structure were accurate.
But here’s the key: Groq’s Dec. 24 statement does not disclose financial details and describes the arrangement as licensing. Reuters also said Groq did not disclose financial details of the deal. [18]
So, while the $20B figure may continue to circulate, it remains unconfirmed by an official acquisition announcement based on the sources available from Dec. 24. [19]
Would this be Nvidia’s biggest deal if it became a full acquisition?
If Nvidia did end up acquiring Groq outright at the reported scale, it would dwarf Nvidia’s prior headline deal-making.
For perspective, Nvidia’s acquisition of Mellanox was announced at approximately $6.9 billion in cash, according to Nvidia’s own newsroom release from 2019. [20]
That historical comparison is why so many headlines used language like “biggest deal ever” when discussing the $20B report: it would represent a step-change in Nvidia’s M&A ambitions.
But again, the Dec. 24 primary statement from Groq is about licensing and leadership transitions—not a signed definitive purchase agreement and not a purchase price. [21]
Jonathan Ross “net worth” goes viral—but private-company math is messy
The deal chatter quickly spilled into a second, more pop-cultural storyline: how rich is Groq founder Jonathan Ross now? A Hindustan Times piece captured the moment, noting that a reported $20B deal would “massively” boost Ross’s net worth and identifying him as Groq’s public face. [22]
However, there are several reasons it’s hard to pin down a reliable figure:
- Groq is private. Founder ownership percentages are not necessarily public, and dilution across funding rounds can be substantial.
- Deal structure matters. A licensing-and-executive move is not the same as a full cash acquisition where equity holders are bought out.
- What’s included matters. Coverage citing investors suggested certain assets might be carved out (such as cloud operations), while Groq’s statement emphasizes GroqCloud continues operating. [23]
In other words: it’s understandable why the net-worth question is trending, but without confirmed financial terms or disclosed equity stakes, any precise number would be speculation.
What to watch next: confirmation, filings, and competitive fallout
The most important next signals for readers and investors aren’t social media reactions—they’re formal confirmations:
- Will Nvidia issue a statement clarifying whether this is strictly licensing + hiring, or something larger? (So far, Reuters reported that neither company commented on the reported $20B acquisition, while confirming the licensing agreement through a source close to Nvidia.) [24]
- Will there be regulatory scrutiny? If the relationship expanded into an outright acquisition, analysts and some market coverage have already raised the possibility of antitrust attention. [25]
- Will Groq keep selling broadly? The deal is explicitly non-exclusive, meaning Groq’s technology could still, in principle, be licensed beyond Nvidia—depending on terms not publicly disclosed. [26]
- What happens to GroqCloud and customers? Groq says operations continue without interruption, which will matter to developers and enterprises that have built inference services around Groq’s platform. [27]
In the bigger picture, this Christmas Eve story—whether it ends up remembered as a misunderstood acquisition headline or as a new model of “AI partnership-plus-talent migration”—highlights a deeper reality: the inference era is here, and Nvidia is moving aggressively to ensure that the chips powering AI responses remain Nvidia-adjacent, even when the underlying architecture isn’t a GPU. [28]
References
1. www.reuters.com, 2. groq.com, 3. www.reuters.com, 4. www.reuters.com, 5. www.reuters.com, 6. groq.com, 7. www.marketwatch.com, 8. groq.com, 9. www.reuters.com, 10. www.reuters.com, 11. techcrunch.com, 12. www.reuters.com, 13. www.reuters.com, 14. groq.com, 15. www.reuters.com, 16. groq.com, 17. www.reuters.com, 18. www.reuters.com, 19. www.reuters.com, 20. nvidianews.nvidia.com, 21. groq.com, 22. www.hindustantimes.com, 23. www.hindustantimes.com, 24. www.reuters.com, 25. www.marketwatch.com, 26. groq.com, 27. groq.com, 28. www.reuters.com
