An analyst says Nvidia’s multi-billion-dollar agreement with Groq is all about securing long-term control over AI inference economics as artificial intelligence moves into real products.
In a new thread on X, Futurum Equities chief market strategist Shay Boloor says Nvidia already dominates AI training and a large share of inference, with its roadmap continuing to push cost-per-token lower while expanding performance through platforms like GB300 and Rubin.
“This was about owning inference economics, not fixing a chip gap.”
The analyst notes that while training is largely a one-time event, inference is where recurring revenue and long-term business models are created as AI systems are deployed into production.
“Training is a one-time event while inference is where the new AI business model lives.”
A key risk for Nvidia, the analyst says, was the possibility that inference could eventually move off GPUs into alternative architectures, eroding Nvidia’s central role over time.
Boloor says Groq was viewed as one of the few credible proofs that latency-sensitive inference could be performed outside the GPU ecosystem, especially given the background of its founder, Jonathan Ross, who previously worked on custom silicon efforts at Google.
“That would have chipped away at Nvidia’s unavoidable status… This deal shuts that door before it could scale.”
The analyst says that while GPUs excel at flexibility and scale, they were never designed to power real-time apps, where latency instability causes cascading failures across workflows.
“That matters because real-world AI breaks when latency jitters: voice assistants pause, live translation lags, agentic workflows compound delays. Groq solved this by designing around large amounts of SRAM by keeping data close to the processor and delivering quick responses every time. That made Groq uniquely suited for real-time AI where latency matters more than peak throughput.”
Boloor concludes that the transaction underscores Nvidia’s evolution from a chip supplier into a vertically integrated AI platform spanning training, networking, and real-time inference.
“At this point, it’s hard to argue Nvidia just sells chips… $20 billion today to avoid a $200 billion problem later.”
Yesterday, reports emerged that Nvidia made its largest purchase to date after inking a $20 billion deal with Groq. The non-exclusive licensing agreement allows Nvidia to use Groq’s inference technology while absorbing senior members of the team, including founder Jonathan Ross and president Sunny Madra.
Disclaimer: Opinions expressed at CapitalAI Daily are not investment advice. Investors should do their own due diligence before making any decisions involving securities, cryptocurrencies, or digital assets. Your transfers and trades are at your own risk, and any losses you may incur are your responsibility. CapitalAI Daily does not recommend the buying or selling of any assets, nor is CapitalAI Daily an investment advisor. See our Editorial Standards and Terms of Use.