Nvidia’s $100 Billion OpenAI Deal Reportedly Collapses
Background of the Nvidia and OpenAI Strategic Alliance
According to reports released by Ars Technica on 3 February 2026, a projected $100 billion arrangement between Nvidia Corporation and OpenAI has failed to materialise, leading to significant fluctuations in market confidence. This development marks a sharp pivot from the trajectory established over the previous decade, during which the two entities maintained one of the most critical symbiotic relationships in the technology sector. The partnership dates back to 2016, when Nvidia co-founder and CEO Jensen Huang personally delivered the first DGX-1 AI supercomputer to OpenAI, an event that is often cited as the catalyst for the modern generative AI era.
Since that initial delivery, OpenAI has relied almost exclusively on Nvidia’s graphics processing units, or GPUs, to train its increasingly complex large language models, including the GPT-4 and GPT-5 architectures. Nvidia, in turn, utilised OpenAI’s success to solidify its position as the primary provider of AI infrastructure, eventually reaching a market capitalisation that rivalled the largest companies in the world. The reported $100 billion deal was expected to be the culmination of this relationship, involving a massive multi-year commitment for next-generation Blackwell and Rubin architecture chips, alongside a direct equity investment component.
The scale of the proposed deal was unprecedented in the semiconductor industry. It was designed to secure OpenAI’s compute requirements for the remainder of the decade, ensuring that the developer of ChatGPT would have priority access to the most advanced silicon available. For Nvidia, the deal represented a guaranteed revenue stream that would have insulated the company against potential cooling in the broader AI market. However, with the deal now described as having “vanished”, industry analysts are closely examining the structural and financial reasons behind the collapse.
Key Developments and the Failure to Materialise
The collapse of the negotiations became apparent when scheduled filings with the Securities and Exchange Commission failed to appear by the end of the first quarter of the 2026 fiscal year. According to industry experts and officials familiar with the matter, the primary friction points involved a combination of valuation disagreements and regulatory hurdles. While the specific terms of the “vanished” deal were never fully publicised, it was widely understood to involve a massive expansion of data centre capacity, often referred to in internal documents as part of a broader infrastructure initiative.
One significant factor in the breakdown appears to be the shifting landscape of AI hardware procurement. While Nvidia remains the market leader, OpenAI has reportedly been exploring the diversification of its supply chain. This includes internal efforts to design custom silicon, a move that mirrors strategies employed by other major technology firms such as Google with its Tensor Processing Units and Amazon with its Trainium chips. The prospect of OpenAI developing its own hardware may have complicated the long-term volume commitments required by Nvidia to justify the $100 billion price tag.
Furthermore, the financial structure of the deal faced scrutiny from institutional investors. The $100 billion figure was not merely a purchase order but a complex framework involving hardware credits, equity swaps, and joint research initiatives. As interest rates remained higher for longer than anticipated in the mid-2020s, the cost of financing such a massive capital expenditure became a point of contention. Reports suggest that the board of directors at both companies could not reach a consensus on the final valuation of the equity portion of the deal, particularly as OpenAI’s internal valuation fluctuated amidst leadership changes and evolving safety mandates.
Impacts on Market Confidence and the AI Ecosystem
The news that the deal has vanished has had an immediate impact on the global financial markets. Nvidia’s share price experienced a sharp correction in after-hours trading following the Ars Technica report, as investors recalibrated their expectations for the company’s long-term data centre revenue. Because Nvidia had been viewed as the primary beneficiary of the AI “arms race”, any sign of a slowdown in its relationship with its most prominent customer is seen as a bellwether for the entire sector.
The broader AI ecosystem is also feeling the repercussions. Many smaller AI startups and venture capital firms have benchmarked their growth projections against the continued expansion of OpenAI’s infrastructure. If the largest player in the space is scaling back its investment or failing to secure necessary hardware at the expected scale, it raises questions about the sustainability of the current investment cycle. Analysts have noted that the “AI bubble” narrative, which has persisted since 2023, has gained renewed traction following this development.
In addition to financial impacts, there are technical implications for the development of Artificial General Intelligence. The $100 billion deal was intended to fund the massive clusters required for the next generation of reasoning models. Without this guaranteed pipeline of Nvidia GPUs, OpenAI may face delays in its training schedules. This potential slowdown provides an opening for competitors, such as Anthropic, Google, and Meta, to close the gap in model performance, provided they can maintain their own hardware supply chains.
Reactions from Industry Analysts and Officials
Market analysts have been quick to weigh in on the implications of the failed deal. Many suggest that the collapse was inevitable given the sheer scale of the capital involved. Experts in the semiconductor industry point out that committing $100 billion to a single partnership creates a level of concentration risk that is difficult for any public company to manage. There are also suggestions that the US Department of Justice and the Federal Trade Commission had been quietly investigating the proposed deal for potential anti-competitive effects, which may have discouraged the parties from proceeding.
Officials within the tech industry, speaking on the condition of anonymity, have indicated that the “vanishing” of the deal might be a strategic pause rather than a permanent severance. However, the lack of a formal statement from either Jensen Huang or Sam Altman has left a vacuum that is currently being filled by market speculation. The silence from both headquarters is uncharacteristic, given their history of high-profile joint appearances at industry keynotes.
Some observers argue that this development is a sign of a maturing market. In this view, the initial period of “irrational exuberance” regarding AI investment is being replaced by a more disciplined approach to capital allocation. Companies are now being asked to demonstrate clear returns on investment for the billions of dollars spent on GPUs. The failure of the Nvidia-OpenAI deal may be the first major example of this new era of fiscal scrutiny in the AI sector.
Next Steps and Future Outlook
The immediate next steps for Nvidia involve reassuring shareholders that its order book remains robust despite the OpenAI setback. The company is expected to highlight its diversifying customer base, including sovereign AI initiatives and the growing demand from automotive and healthcare sectors. Nvidia’s upcoming earnings call will likely be dominated by questions regarding the status of its relationship with OpenAI and whether other large-scale “hyperscaler” deals are at risk.
For OpenAI, the focus will likely shift toward its internal chip development programme and its partnership with Microsoft. Microsoft, which has invested billions into OpenAI, may be required to step in and provide the necessary infrastructure through its Azure cloud platform, potentially using its own “Maia” AI chips to supplement any shortfall in Nvidia hardware. This could lead to a realignment of the “three-way” relationship between Nvidia, Microsoft, and OpenAI, with Microsoft taking a more central role in hardware provision.
In the long term, the vanishing of this $100 billion deal may accelerate the industry’s move toward more efficient AI architectures that require less compute power. If the cost of scaling through raw hardware becomes prohibitive, the focus of research may shift toward algorithmic efficiency and smaller, more specialised models. While the immediate reaction to the news is one of uncertainty, the eventual outcome may be a more sustainable and diversified AI infrastructure landscape. Details regarding any potential renegotiation or alternative arrangements remain unclear at this time, as both companies have declined to provide official comments on the Ars Technica report.