Nvidia has quietly transformed itself from the world’s dominant maker of artificial intelligence chips into one of the sector’s most powerful financiers, pouring tens of billions of dollars into startups across the AI ecosystem as it seeks to cement its role at the center of the technology boom.
Until February, flush with cash from surging demand for its graphics processors, the $4.4 trillion company had invested roughly $53 billion across about 170 deals spanning everything from large language model developers and AI cloud providers to robotics, chip design tools and quantum computing firms, according to PitchBook data.
The company participated in nearly 67 venture rounds in 2025, up from 54 in 2024 and just 12 in 2022.
NVentures alone completed 30 deals last year.
Model builders backed by Nvidia include OpenAI, Anthropic, Mistral, Cohere, Thinking Machines Lab and Elon Musk’s xAI.
The company has also invested in cloud and computing infrastructure providers such as CoreWeave, Nscale and Nebius.
Beyond the core AI stack, Nvidia has also backed companies focused on autonomous driving, robotics and advanced computing technologies.
Autonomous vehicle startup Wayve, robotics developer Figure AI and chip design software maker Synopsys have all received investments.
Nvidia took a $2 billion equity stake in Synopsys in December.
The company has also invested in emerging technologies such as quantum computing company Quantinuum and nuclear fusion startups.
Nvidia’s busy March: Nebius, Murati startup and photonics deals
On Wednesday, the company said it would invest $2 billion in AI cloud company Nebius.
As part of the agreement, the two companies will collaborate on deploying large-scale AI infrastructure, including data center operations, fleet management, inference systems and AI factory design.
The partnership also gives Nebius early access to Nvidia’s latest accelerated computing platforms as it seeks to deploy more than five gigawatts of computing capacity by the end of the decade.
A day earlier, Nvidia also announced a significant investment in Thinking Machines Lab, the artificial intelligence startup founded by former OpenAI chief technology officer Mira Murati.
Thinking Machines Lab raised $2 billion in seed funding last year in a round that valued the company at $12 billion.
Nvidia was among the investors participating in the round as part of a multiyear strategic partnership.
Murati, who briefly served as interim chief executive of OpenAI during the leadership turmoil in 2023, founded the company last year.
The startup aims to develop AI systems that are more customizable and easier for users to understand, although details about its long-term plans remain limited.
Earlier this month, the company announced plans to invest $2 billion each in photonics manufacturers Lumentum and Coherent.
The investments are aimed at improving the optical networking technologies needed to move vast amounts of data between AI processors in data centers.
Shares in both companies rose sharply following the announcement, reflecting investor optimism about the growing demand for infrastructure that can support increasingly powerful AI chips.
Major bets on leading AI developers – OpenAI, Anthropic, xAI
Among Nvidia’s largest investments are those in major AI model developers, including OpenAI and Anthropic.
Last month, Nvidia invested $30 billion in OpenAI as part of a $110 billion funding round that also included Amazon and SoftBank.
Nvidia had first backed OpenAI in October 2024 with a $100 million investment as part of a $6.6 billion funding round that valued the company at $157 billion.
The two companies also announced a major infrastructure partnership last year to deploy at least 10 gigawatts of Nvidia computing systems for training and running OpenAI’s next generation of AI models.
Nvidia said it intended to invest up to $100 billion in OpenAI to support this deployment.
However, Nvidia chief executive Jensen Huang suggested earlier this month that the company may not increase its financial exposure to OpenAI much further as the startup prepares for a potential initial public offering later this year.
Huang said the opportunity to invest $100 billion in OpenAI is probably “not in the cards.”
“The reason for that is because they’re going to go public,” Huang said during the Morgan Stanley Technology, Media and Telecom Conference.
Nvidia has also invested heavily in Anthropic, a major rival to OpenAI.
In November 2025 the company committed up to $10 billion as part of a strategic funding round that also included a $5 billion investment from Microsoft.
Under a related agreement, Anthropic committed to spending $30 billion on Microsoft’s Azure cloud infrastructure and purchasing Nvidia’s next-generation Grace Blackwell and Vera Rubin AI systems.
However, for Anthropic too, Huang said earlier this month, that the $10 billion investment would likely be Nvidia’s last.
In January, Nvidia pariticpated in the $20 bn funding round for Elon Musk’s xAI.
It also participated in the $6 billion round of xAI last December.
Expansion of investments into Europe
Nvidia has expanded its investment strategy beyond the United States as well, particularly in Europe.
The company participated in 14 funding rounds for European technology companies last year, according to Dealroom data, up from seven deals in 2024 and just one in 2022.
Among the most prominent European investments is French AI startup Mistral.
Nvidia participated in the company’s €1.7 billion Series C funding round in September, which valued the firm at €11.7 billion.
Mistral is widely viewed as one of Europe’s leading artificial intelligence developers, building models designed to compete with systems from companies such as OpenAI and Alphabet.
In the United Kingdom, Nvidia has backed AI infrastructure company Nscale, committing £500 million to the startup as it builds data centers and cloud computing capacity tailored for AI workloads.
The company has also invested in European firms including Quantinuum, Lovable and Black Forest Labs.
Strategy aims to expand Nvidia’s AI ecosystem
Huang has said the investments are designed to strengthen Nvidia’s software and hardware ecosystem while accelerating the broader development of artificial intelligence technologies.
“All of the investments that we’ve done so far — all of it, period — is associated with expanding the reach of CUDA, expanding the ecosystem,” Huang said, referring to Nvidia’s AI software platform.
While Nvidia does not formally require companies it invests in to purchase its hardware, most of them rely on its chips for their AI infrastructure.
Analysts say the strategy helps ensure long-term demand for Nvidia’s products while reducing dependence on a handful of large technology customers.
Critics warn of circular investment risks
However, Nvidia’s investments have also drawn scrutiny from some analysts and investors who argue that the strategy could create circular flows of capital within the AI industry.
Because many of the companies Nvidia invests in also purchase its chips or computing services, critics say the arrangements resemble vendor financing practices seen during the technology bubble of the late 1990s.
Short sellers Jim Chanos and Michael Burry have compared Nvidia’s strategy to the approach used by telecom equipment maker Lucent Technologies during the dot-com boom.
Lucent provided financing to customers who used the funds to purchase its equipment, a model that collapsed when the bubble burst.
Nvidia has rejected those comparisons.
In a detailed memo sent to Wall Street analysts last year, the company argued that its investments and product sales are separate and that its customers typically pay for hardware within 53 days.
Strong cash position enables aggressive investment
With a large and growing cash reserve, Nvidia has significant financial flexibility to pursue its investment strategy.
The company held about $62.56 billion in cash, cash equivalents and short-term investments as of its most recent quarterly reports.
Some analysts believe deploying that capital into AI startups may be one of the best uses of Nvidia’s resources during a period of rapid industry growth.
Bernstein analyst Stacy Rasgon told Yahoo Finance there may be “no better use of Nvidia’s cash right now,” although he acknowledged that the strategy could raise concerns among investors.
Others caution that the approach could expose Nvidia to risks if the current surge in demand for AI computing capacity slows.
“If AI demand in 2027 or 2028 falls short of today’s projections, you could see orders begin to be canceled, and that’s a big risk that not a lot of people are talking about,” warned Chanos.
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