Nvidia is primarily known as a chip company. It designs the GPUs that power AI training and inference, and it currently holds somewhere between 80 and 90% of the AI accelerator market. If you want a full picture of what Nvidia’s business actually covers, What Does Nvidia Really Do? goes into that in depth. So when it started writing large equity cheques into software companies like OpenAI, Mistral, Anthropic, and xAI, it raised a reasonable question: why is a hardware company putting billions into software startups?
The answer is not as complicated as the investment activity makes it look. There are three reasons, and each one reinforces the others.
The Short Answer
Nvidia invests in AI startups to create and sustain demand for the one product it makes most of its money from: GPUs. It also invests to ensure that no matter which AI company or model wins the race, the winner runs on Nvidia hardware. And it invests because it generates so much cash from selling chips that redeploying that capital in to the AI ecosystem is simply the most effective use of it. These three motivations work together rather than separately, and together they explain why Nvidia participated in 67 venture capital deals in 2025 alone and deployed $23.7 billion across 59 transactions that year.
Reason 1: The Investments Create Direct Demand for Nvidia’s Own Chips
This is the most important reason, and it is also the one that looks the most circular, because it is.
The pattern is straightforward: Nvidia pours capital into AI startups and cloud providers, then they turn around and spend heavily on Nvidia GPUs, either directly or through hyperscaler partners. Nvidia gives a startup money. The startup uses that money to build AI systems. Those AI systems run on Nvidia hardware. Nvidia sells more GPUs. The revenue from those GPU sales funds the next round of investments. Then the cycle repeats.
The xAI investment illustrates this cleanly. Nvidia committed up to $2 billion in the equity portion of xAI’s $20 billion funding round, and the deal was structured explicitly to help xAI purchase more Nvidia hardware. That is not a hidden arrangement. It is the stated purpose of the investment. Nvidia funds the customer so the customer can buy the product.
In its most recent reported quarter, Q1 fiscal 2027, which ended April 2026, Nvidia reported $18.6 billion deployed into AI companies and $15.9 billion in portfolio gains in the same period. The investments are not a sideshow to the chip business. At this scale, they are inseparable from it.
Reason 2: Nvidia Is Betting on the Entire Race, Not a Single Winner
Nvidia has invested in OpenAI, Anthropic, Mistral, and xAI. These companies are all building large language models and AI agents, covered in detail in What Is an AI Agent?, and they compete for the same enterprise customers. Nvidia invested in all of them.
Nvidia’s logic is that it does not need to bet on a single winner. It needs to bet on the entire track. If OpenAI wins the model race, Nvidia wins because OpenAI trains on Nvidia GPUs. If Anthropic wins, Nvidia wins. If Mistral builds the leading European AI platform and runs it on Nvidia processors, as announced at the VivaTechnology conference in June 2025, Nvidia wins that outcome too. The only scenario where Nvidia loses is the one where someone builds a competitive AI infrastructure that does not rely on Nvidia chips. By investing across every major AI lab, Nvidia reduces the likelihood of that outcome and ensures it has a seat at every table regardless of who ends up leading.
Between 2021 and 2025, Nvidia participated in funding rounds for 241 different companies. All ten of the most-funded AI startups on the Forbes AI 50 list received Nvidia investment. That breadth is not coincidental. It reflects a deliberate decision to hold a position in the AI ecosystem broadly rather than concentrate on any one direction it takes.
Reason 3: Nvidia Has More Cash Than It Knows What to Do With
This reason sounds flippant, but it is the assessment of analysts who cover the company directly.
Nvidia generated $62.3 billion in data centre revenue in Q4 fiscal 2026 alone, up 75% from the prior year. At that scale of cash generation, sitting on capital is itself a strategic decision with an opportunity cost. Reinvesting it into the AI ecosystem that generates GPU demand is a more effective use of it than most alternatives. An analyst at CNBC described Nvidia’s investments as mirroring its broader global strategy of taking excess cash and reinvesting it in the AI ecosystem across a host of startups.
The returns on that strategy have been material. In Q1 fiscal 2027, Nvidia reported $15.9 billion in portfolio gains from its AI company investments, which contributed directly to its balance sheet alongside the chip revenue. The investments are not charitable. They are producing financial returns on top of the demand-creation benefit.
The Honest Caveat: Critics Call It Circular
The strategy is not without criticism, and the criticism is worth stating plainly.
Analysts at 24/7 Wall St and elsewhere describe Nvidia’s approach as circular investment, essentially vendor financing on steroids, where Nvidia is funding a significant portion of its own demand. If Nvidia’s investment faucet were turned off, a material portion of chip orders could shrink alongside it. That raises questions about how much of the AI infrastructure boom reflects organic demand versus Nvidia-funded demand. Regulators in the US and EU have also noted the pattern, with scrutiny increasing over Nvidia’s growing vertical integration across chips, cloud infrastructure, and now equity stakes in major AI labs.
Even Bernstein analyst Stacy Rasgon, who covers Nvidia closely, acknowledged the optics concern while calling the strategy a savvy use of Nvidia’s enormous cash pile to cement ecosystem dominance in a winner-take-most market. The strategy works as long as AI infrastructure demand keeps growing. The risk is what happens if it slows.
There is also a shift underway. In March 2026, speaking at the Morgan Stanley TMT conference, Jensen Huang described the OpenAI and Anthropic investments as likely Nvidia’s last major private-lab bets, because both companies are expected to go public in 2026 and the private investment window closes once that happens. The strategy is evolving from backing AI labs to backing GPU-rental infrastructure providers like CoreWeave and Nebius, which aggregate large hardware purchases and represent the next phase of the same flywheel.
FAQs
Why did Nvidia invest in OpenAI specifically? Nvidia made its first investment in OpenAI in October 2023, contributing to a $6.6 billion round that valued OpenAI at $157 billion. The later commitment grew to approximately $30 billion. OpenAI is the largest consumer of AI compute in the world, and it trains and runs its models on Nvidia GPUs. Investing in OpenAI is, in practical terms, investing in the company that buys more Nvidia hardware than almost any other organisation on the planet.
Why did Nvidia invest in Mistral AI three separate times? Mistral is building what it describes as Europe’s leading AI infrastructure, and it is doing so explicitly on Nvidia processors. In June 2025, Mistral announced the creation of Mistral Compute, a European AI platform powered by Nvidia hardware, an initiative announced jointly by Mistral CEO Arthur Mensch and Jensen Huang at the VivaTechnology conference in Paris. Nvidia investing in Mistral three times is consistent with its strategy of backing the companies most likely to drive long-term European GPU demand.
Does Nvidia investing in AI startups create a conflict of interest? It creates a structural entanglement that regulators are examining. Nvidia holds equity in major AI labs that are also its largest customers, which means its financial interest in those companies is tied to their GPU purchases. Critics describe this as circular demand creation. Nvidia’s position is that it is reinvesting excess cash to accelerate the AI ecosystem it benefits from. Both characterisations are accurate. The tension between them is one of the reasons US and EU regulatory bodies have opened broader reviews of AI supply chain integration.
Is Nvidia still investing in AI startups the same way in 2026? The approach is shifting. Huang indicated in March 2026 that the major private-lab investments in OpenAI and Anthropic were likely the last of their kind, given the expected public listings of both companies. The investment focus is moving toward neocloud and GPU-rental providers such as CoreWeave, Nebius, and Nscale, which buy and rent large quantities of Nvidia hardware, as well as infrastructure companies across cooling, optical fibre, and data centre supply chains. The flywheel logic is the same. The specific companies in the portfolio are changing.
Key Takeaway
Nvidia invests in AI startups because doing so makes its core chip business more valuable. Every dollar that goes into an AI lab or cloud provider tends to come back as GPU orders increases. Every AI company it backs reduces the chance of a future where AI is built on someone else’s hardware. And with the kind of cash Nvidia is generating, redeploying it into the ecosystem is a more effective strategy than almost any alternative.
The circularity of that strategy is real and worth watching. But at $62.3 billion in quarterly data centre revenue and $15.9 billion in portfolio gains in a single quarter, it is also, for now, working.
