NVIDIA and OpenAI are all that's being talked about in the AI world, not because there have been changes in their commitments, but because the scale of the partnership is so immense that it captures all the market spotlight.
Before we dive into the ongoing NVIDIA-OpenAI fiasco, it's important to note the fundamentals that underpin the partnership. Team Green is currently the world's largest AI infrastructure provider, and almost all hyperscalers are dependent on the company, not just for hardware, but also for financial commitments in the form of "collaborations" or whatever you call it. At the same time, NVIDIA has ramped up its external investments in frontier labs, such as Anthropic and OpenAI, mainly because Jensen claims their work is "revolutionary enough" to warrant investment.
When you are as big as NVIDIA, it's important to keep key entities close, and in the case of OpenAI, Sam Altman has enjoyed an exclusive relationship with Jensen, not just in finance but also in compute access. This relation reached a decisive point when NVIDIA decided to invest up to $100 billion into a "non-binding", "inconclusive", "not final" arrangement, and it is really important to keep a focus on the words that I have highlighted previously. OpenAI's successful GPT-5 release drove NVIDIA's investment, but in recent days, market speculation and industry chatter suggest that internal sentiment towards OpenAI has changed.
Now, there are two major aspects to this story that we'll cover. The first and more important is, of course, the compute factor, while the other is whether both sides are getting a "worthy" investment/collaboration. The second reason coexists with the first, but by highlighting it separately, we can discuss industry dynamics on a much broader scale, helping our readers realize that the actual situation is far bigger than what's being discussed.
The Compute Factor: Sam Altman Might Be Thinking 10GW Priced at $100 Billion Might Not Be the Best Choice
Let me define 'compute factor' more extensively. Since it's all about the infrastructure race, companies are racing to secure the best TCOs by either pursuing NVIDIA on attractive deals or exploring the ASIC route, hoping to lower operating costs or at least convince NVIDIA to get into an agreement. One of the major highlights of the NVIDIA-OpenAI arrangement was the supply of Vera Rubin clusters, in a deal worth $100 billion, which would bring on 10GW of capacity to power "OpenAI's next-generation AI infrastructure".
On a surface level, the arrangement sounds optimal, since, as OpenAI, you are essentially getting exclusive access to and commitment from the world's largest GPU company, that too as you head into the pre-IPO phase. For NVIDIA, well, their next-gen hardware is validated by one of the world's largest frontier labs, allowing them to drive hyperscaler and the interests of other segments. But here's when things take a twist, and I'll justify this. With Vera Rubin, per GW capacity, it comes to around $10 billion, based on what we have seen with official PRs.
Today's Reuters report suggests that OpenAI found NVIDIA's chips not 'worthwhile' enough, and that the company even had plans to explore deals with manufacturers like Groq and Cerebras, despite not being involved in the AI infrastructure race at all. While Sam Altman himself has denied such claims, there is no doubt that within the company's ranks, there is skepticism towards whether NVIDIA's partnership yields the optimal outcome, in terms of the $/GW capacity coming onboard.
When you see OpenAI eying Groq or Cerebras, the idea, of course, is to leverage inference and latency over NVIDIA's tech stack by finding a middle ground. Reuters also suggested that OpenAI feels NVIDIA lags in inference, and that the AI lab would need "hardware that would eventually provide about 10% of OpenAI's inference computing needs".
Cerebras is supplying OpenAI with 750MW of capacity at around $10 billion, which, yet again, isn't optimal when you look at per-GW figures versus NVIDIA. But the race here is defintely towards who gets the better deal on the compute front, as seen in today's Reuters report. Yet again, neither party has discussed this at all, and when both Jensen and Altman were asked about their commitments to each other, both said they are on track with the initial plan.
The Industry Factor: Combine Market Chatter, OpenAI’s Recent Performance, and Jensen’s Comments, and You Get a Messy Salad
The recent NVIDIA-OpenAI talks, especially regarding the commitments being switched up, are part of a "narrative" that NVIDIA has already discussed. We double-checked NVIDIA's PR, 10-Q filing, and CFO Colette Kress's statements, and realized that NVIDIA never actually decided to invest $100 billion in OpenAI directly; instead, it was a multi-GW plan divided into multiple milestones. With each milestone, NVIDIA would ramp up its investments, and the total would reach $100 billion; hence, there wasn't a one-time payment commitment.
To support the partnership, NVIDIA intends to invest up to $100 billion in OpenAI progressively as each gigawatt is deployed. (NVIDIA's PR)
There is no assurance that we will enter into definitive agreements with respect to the OpenAI opportunity or other potential investments, or that any investment will be completed on expected terms (10-Q filing)
A reporter asked NVIDIA's CEO Jensen Huang about the status of the OpenAI deal, and many viewers over the internet felt that Huang was 'agitated' by the questions, claiming that the reporter was "putting words in his mouth", which expresses his frustration towards recent market rumors. Huang also stated that it wouldn't be wise to commit to OpenAI, and that the company will still make its largest-ever investment into the AI lab.
We never said we would invest $100B in one round. There was never a commitment. They invited us to invest up to $100B. We will invest one step at a time.
I told you just now. You keep putting words in my mouth.
- NVIDIA's Jensen Huang
At NVIDIA's front, the idea that the OpenAI deal was a 'non-binding' agreement seems solidified, so on the other side, let's look at what's up at Sam Altman's camp. Well, first off, the company is losing the race in the agentic AI era right now, as Anthropic's Claude takes a lead, credited to its robust 'applications layer' with Claude Code, Claude Cowork, and many wrappers built around Opus 4.5. Given that OpenAI has held a lead in the AI market for several years now, the sudden competition has sparked speculation about the AI lab's future.
More importantly, OpenAI is racing towards an IPO this year, aiming to raise immense capital to become the first AI lab to go public and potentially cross the $500 billion market capitalization threshold. The pre-IPO phase is proving difficult for OpenAI at the moment, as revenue projections are falling, raising concerns about whether the company's $1.4 trillion in commitments over the next decade can be fulfilled. Combine all the above talks, and you'll realize that the NVIDIA-OpenAI story is all around speculation for now.
There are many industry elements and strategies to keep in mind when you look at the current AI landscape, and when you factor in politics within businesses, you'll realize that the OpenAI-NVIDIA discussions carry a lot of weight. For now, both parties are fully committed, but it would be interesting to see how the future unfolds.
About the author: Muhammad Zuhair is a hardware and technology reporter for Wccftech, specializing in the semiconductor industry and the complex interplay between technology, manufacturing, and geopolitics. His coverage focuses on the corporate strategies and technological roadmaps of industry giants like TSMC, NVIDIA, Samsung, and Intel. Zuhair's expertise lies in deconstructing complex topics such as fabrication nodes (e.g., 2nm process), the economic impact of policies like the CHIPS Act, and the strategic development of AI infrastructure from NVIDIA, AMD and Intel.
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