The NVIDIA-OpenAI Fiasco Isn’t About Computing, It’s About Control; Here’s How Some of the World’s Greatest Partnerships Play for AI

NVIDIA and OpenAI are all the talk of the AI ​​world, not because there have been changes in their commitment, but because the scale of the partnership is so large that it captures all the market spotlight.

Before we get into the ongoing NVIDIA-OpenAI fiasco, it’s important to note the basics that underpin the partnership. Team Green is currently the largest AI infrastructure provider in the world, and almost all hyperscalers depend on the company, not only for hardware, but also for financial commitment in the form of “collaboration” or whatever you call it. At the same time, NVIDIA has increased its external investment in frontier labs, such as Anthropic and OpenAI, mainly because Jensen says their work is “flexible enough” to justify the investment.

When you’re as big as NVIDIA, it’s important to keep important organizations close, and in the case of OpenAI, Sam Altman enjoyed a special relationship with Jensen, not only in finance but also in computing. This relationship reached a decisive point when NVIDIA decided to invest up to $100 billion in a program that is “non-binding”, “incomplete”, “not final”, and it is very important to focus on the words I highlighted earlier. OpenAI’s successful release of GPT-5 spurred NVIDIA’s investment, but in recent days, market speculation and industry discussion suggest that the internal sentiment about OpenAI has changed.

Now, there are two major aspects to this story that we will cover. First and foremost, of course, is the compute factor, and the other is that both parties get a “fair” investment/cooperation. The second reason is related to the first, but by highlighting it separately, we can discuss the changes in the industry on a much broader scale, helping our readers to see that the real situation is much bigger than what is being discussed.

Compute Factor: Sam Altman May Think 10GW Priced at $100 Billion May Not Be the Best Choice

Let me explain the ‘compute factor’ in more detail. Since it’s all about the infrastructure race, companies are racing to secure the best TCOs by pursuing NVIDIA in attractive deals or exploring the ASIC route, hoping to lower operating costs or at least convince NVIDIA to enter into a deal. One of the highlights of the NVIDIA-OpenAI program was the provision of the Vera Rubin clusters, in a deal worth $100 billion, which will deliver 10GW of “Next Generation OpenAI AI Infrastructure”.

At a high level, the arrangement sounds good, as, like OpenAI, you actually get exclusive access and commitment from the world’s largest GPU company, and that too as you enter the pre-IPO stage. For NVIDIA, well, their next-generation hardware is verified by one of the largest labs in the world, which allows them to drive hyperscaler and the interests of other segments. But here is where things change, and I will forgive this. With Vera Rubin, the volume of each GW, comes to about 10 billion dollars, based on what we have seen with official PRs.

Today’s Reuters report suggests that OpenAI found NVIDIA’s chips to be ‘not good enough’, and that the company had plans to test deals with manufacturers such as Groq and Cerebras, despite not being involved at all in the AI ​​infrastructure race. Although Sam Altman himself denies these allegations, there is no doubt that among the companies, there is doubt as to whether the NVIDIA partnership is producing a positive result, in terms of the upcoming $/GW capacity.

If you see OpenAI looking at Groq or Cerebras, the idea, of course, is to use guesswork and latency on top of NVIDIA’s technology stack by finding a middle ground. Reuters also suggested that OpenAI feels that NVIDIA is lagging behind, and that the AI ​​lab will need “hardware that will eventually provide about 10% of OpenAI’s computing needs”.

Cerebras provides OpenAI with 750MW of capacity estimated at 10 billion dollars, which, again, is not fair if you look at the figures per GW compared to NVIDIA. But the race here is to see who will get the best deal ever, as seen in today’s Reuters report. Again, neither team has discussed this, and when both Jensen and Altman were asked about their commitments to each other, both said they were on track with the original plan.

The recent NVIDIA-OpenAI discussions, especially regarding the exchange commitments, are part of the “narrative” that NVIDIA has already discussed. We double-checked NVIDIA’s PR, 10-Q, and CFO Colette Kress’s statements, and we saw that NVIDIA didn’t actually decide to invest $100 billion in OpenAI directly; instead, it was a multi-GW system divided by multiple milestones. With each milestone, NVIDIA will increase its investment, and the total will reach $100 billion; therefore, there was no one-time payment commitment.

To support the partnership, NVIDIA intends to invest up to $100 billion in OpenAI in the future as each gigawatt is used. (NVIDIA’s PR)

There can be no assurance that we will enter into definitive agreements regarding the OpenAI opportunity or other potential investments, or that any investment will be completed on anticipated terms (10-Q filings).

The reporter asked NVIDIA CEO Jensen Huang about the status of the OpenAI agreement, and many viewers on the Internet felt that Huang was “irritated” by these questions, saying that the reporter was “putting words in his mouth”, expressing his frustration with the latest rumors in the market. Huang also pointed out that it would be unwise to commit to OpenAI, and that the company is yet to make its largest ever investment in an AI lab.

We never said we would invest $100B in one round. There was never any commitment. They invited us to invest up to $100B. We will invest one step at a time.

I told you now. You keep putting words in my mouth.

– Jensen Huang of NVIDIA

On the NVIDIA front, the idea that the OpenAI agreement was a ‘non-binding’ agreement seems strong, so on the other hand, let’s look at what is happening in Sam Altman’s camp. First, the company is losing the race in the AI ​​era of the agency right now, as Claude of Anthropic leads, marked by a strong ‘applications layer’ with Claude Code, Claude Cowork, and many wrappers built around Opus 4.5. Given that OpenAI has held the lead in the AI ​​market for several years now, this sudden competition has sparked speculation about the future of the AI ​​lab.

More importantly, OpenAI is racing toward an IPO this year, aiming to raise capital to become the first AI lab to go public and potentially surpass the $500 billion market capitalization threshold. The pre-IPO phase is looking tough for OpenAI right now, as revenue numbers are falling, raising concerns about whether the company’s $1.4 billion in commitments over the next decade can be met. Put all the above statements together, and you will see that the NVIDIA-OpenAI story revolves around speculation at the moment.

There are many industry and strategy factors to keep in mind when looking at the current state of AI, and if you focus on the politics within businesses, you will see that the OpenAI-NVIDIA negotiations carry a lot of weight. For now, both sides are fully committed, but it will be interesting to see how the future unfolds.

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