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Nvidia offers start-up customers chance to swap compute power for revenue share
Chipmaker Nvidia says it is entering revenue-sharing agreements with fast-growing start-ups, in a move which will see customers swap access to compute power for a slice of future profits. The artificial intelligence chip leader says its new partnership program, announced Thursday, offers fast-growing AI startups token credits to power their development. Cloud-based AI firms, model builders and other enterprises will share both product and cloud revenue with Nvidia, which is positioning itself as an intermediary helping startups gain direct access to full-stack computing powered by Nvidia chips. In its announcement, Nvidia named two initial partners who will provide the compute power behind the scheme. Australia-based Sharon AI will deploy up to 40,000 Nvidia GPUs, while Singapore AI infrastructure company Firmus Technologies says it is building a data center in Batam, Indonesia, which is expected to scale to 360 megawatts and house up to 170,000 Nvidia GPUs. Nvidia's move illustrates the critical importance of access to scarce compute power for AI-oriented startups, with GPUs likened to oil and even reportedly tied to futures contracts as users grapple with fluctuations in cost and issues around availability. Meanwhile, AI firms have increasingly entered into revenue and equity-sharing sharing agreements with chipmakers in order to circumvent liquidity issues afflicting the sector. OpenAI has inked a number of deals that have seen it buy shares or entertain investments from partners including Amazon and AMD, CNBC reported in January. Nvidia earlier this month said it was aiming to raise debt which sources said could amount to at least $20 billion. The firm intends to use the proceeds from the offering for general corporate purposes, including repayment and refinancing of existing debt.
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Nvidia offers AI startups compute now, payment later
Instead of just selling chips, Nvidia is offering AI clouds a revenue-sharing and credit-support model built to get GPUs into the hands of companies that could not otherwise afford them. Nvidia is changing how it gets paid. The company announced on Wednesday a new arrangement in which AI cloud providers can access large volumes of its chips in exchange for a share of the revenue those chips eventually generate, rather than paying the full cost upfront. The logic, as Nvidia frames it, is a capital problem. Emerging AI companies have historically had limited access to the capital-intensive infrastructure needed to train and run large models, and even long-term customer commitments have often not been enough to unlock financing for compute. Nvidia's answer is to let AI clouds buy its hardware and resell Nvidia-powered cloud capacity, with Nvidia collecting standard product revenue on the chips and then a further cut of whatever the cloud earns from renting them out. It is the same compute crunch that has sent valuations soaring for GPU resellers like Runpod, which hit a $1 billion valuation this June renting out chips it does not own. Two companies are already running on the model. Sharon AI, an Australian AI cloud operator, is deploying up to 40,000 Nvidia Grace Blackwell GB300 GPUs across a six-year, 72-megawatt agreement, a deal its cofounder and chief executive James Manning called "a pivotal moment" for the company's push into sovereign, large-scale AI compute. Firmus, the other early partner, is building a much larger campus. The Australian firm is developing a 360-megawatt Nvidia DSX AI factory in Batam, Indonesia, that will eventually house up to 170,000 GPUs across Nvidia's Grace-Blackwell, Vera-Rubin and Vera platforms. Bloomberg has reported that Firmus expects between $25 billion and $30 billion in committed offtake agreements over the deal's first six years, a scale that only makes sense if compute demand from AI-native customers keeps climbing. Nvidia named Baseten, Fireworks AI and Together AI as examples of the customers this is meant to serve. These are companies that need immediate, elastic access to AI cloud capacity for training, fine-tuning and high-volume inference without committing to years of hardware procurement themselves, a different customer to the hyperscalers Nvidia has courted for a decade. It is a bet on the long tail of model builders, agent platforms and enterprises that want frontier compute but not the balance-sheet risk of building a data centre. The arrangement also gives Nvidia something it has not had at this scale before, a recurring, usage-linked income stream layered on top of hardware sales. The model pairs revenue sharing with credit support, effectively helping smaller AI clouds finance the purchase in the first place. It is not a loan, but it functions like vendor financing with an equity-like upside attached. None of this changes what Nvidia sells, and the chips still cost what they cost. What changes is who can afford to buy them and on what terms, which matters more than it sounds. Site selection, power procurement, construction and hardware bring-up can take years before a startup ever runs a workload, and Nvidia's pitch is that AI cloud partners can compress that timeline by selling capacity that already exists. The company has already committed more than $40 billion to direct AI equity investments this year, spanning OpenAI, Nebius and dozens of smaller rounds. A revenue-sharing compute model does something similar without touching the cap table, keeping the balance sheet exposure with its cloud partners instead of on its own books. Nvidia has not disclosed how many AI clouds it expects to sign on this basis, or whether the Sharon AI and Firmus terms will be standardised across future partners. It also deepens a dependency that has already drawn scrutiny, as an increasing share of the AI industry's growth becomes contractually tied to Nvidia's own success. If the model works, more compute reaches more startups faster than the traditional buy-it-outright approach allowed. If AI-native demand cools, Nvidia is now exposed to that slowdown twice, once through chip sales and again through the cloud revenue it has agreed to share.
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Nvidia Is Making it Easier for AI Startups to Get Compute Power With a New Cloud and Revenue-Sharing Prog
The Jensen Huang-led company announced on Wednesday that the AI cloud providers would offer services powered by Nvidia technology under this program. This setup enables Nvidia to profit from hardware sales and a share of the cloud providers' future earnings. The initiative aims to alleviate the financial challenges encountered by emerging AI firms requiring access to expensive computing infrastructure. Several cloud providers, including Sharon AI and Firmus, are among the first to build AI infrastructure using Nvidia's DSX data center platform under the program's initial rollout. Sharon AI plans to deploy up to 40,000 NVIDIA Grace Blackwell GB300 GPUs, while Firmus is developing a DSX AI factory campus in Batam, Indonesia. Nvidia is expanding its AI ecosystem by investing in cloud and data center partnerships, helping emerging AI companies adopt its processors and broaden the use of its technology amid growing demand for AI computing. Nvidia's AI Push Divides Experts Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.
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Nvidia offers revenue sharing agreements for AI startups By Investing.com
Investing.com-- Nvidia said on Wednesday it was offering artificial intelligence startups computing resources through a revenue-sharing and credit-support model. The company said in a press release that through the partnership, AI cloud providers will sell Nvidia-powered cloud services, granting the company both standard product revenue and a share of the cloud earnings. Get more breaking news on Nvidia and other top AI stocks by subscribing to InvestingPro Nvidia said the new arrangements were aimed at providing emerging AI companies with access to the capital-intensive infrastructure they would otherwise need vast amounts of funds to access. The AI major said cloud companies were already building AI centers on its DSX data center platform, with Sharon AI and Firmus being among the first companies to work with Nvidia through the new business model. The business model comes as Nvidia engages in a flurry of major AI and data center deals to further development in the fast-growing technology, while also gaining more customers for its advanced AI processors. AI and data center demand brought Nvidia a major windfall over the past three years, helping balloon its valuation to the become biggest company on Wall Street.
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Nvidia launched a revenue-sharing program that lets AI startups access expensive GPU compute power without upfront costs. Instead of buying chips outright, cloud providers can deploy Nvidia hardware and share future cloud earnings with the chipmaker. Sharon AI is deploying 40,000 Grace Blackwell GPUs, while Firmus is building a 360-megawatt facility in Indonesia with up to 170,000 GPUs, addressing capital barriers that have limited AI development.
Nvidia announced Wednesday a new business model that fundamentally changes how AI startups access expensive computing infrastructure. Rather than requiring companies to purchase chips upfront, the revenue-sharing program allows cloud providers to deploy Nvidia GPUs and share future cloud earnings with the chipmaker
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. The initiative targets fast-growing AI startups, model builders, and cloud-based AI firms that need immediate access to compute capacity but lack the capital for large hardware investments2
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Source: Benzinga
The credit-support model addresses what Nvidia frames as a capital problem: emerging AI companies have historically struggled to access the capital-intensive infrastructure needed to train and run large models, even when they have long-term customer commitments
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. By positioning itself as an intermediary, Nvidia helps startups gain direct access to full-stack computing while collecting both standard product revenue on chip sales and a cut of whatever the cloud earns from renting them out1
.Two companies are already building AI infrastructure under the new arrangement using Nvidia's DSX data center platform. Sharon AI, an Australian AI cloud operator, is deploying up to 40,000 Grace Blackwell GB300 GPUs across a six-year, 72-megawatt agreement
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. James Manning, Sharon AI's co-founder and CEO, called it "a pivotal moment" for the company's push into sovereign, large-scale AI compute2
.Firmus Technologies is pursuing an even larger deployment. The Singapore-based AI infrastructure company is building an AI factory campus in Batam, Indonesia, expected to scale to 360 megawatts and house up to 170,000 Nvidia GPUs across Grace-Blackwell, Vera-Rubin and Vera platforms
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. Bloomberg reported that Firmus expects between $25 billion and $30 billion in committed offtake agreements over the first six years2
.The arrangement functions similarly to vendor financing with equity-like upside attached, though it's not technically a loan
2
. Cloud providers can access large volumes of chips in exchange for sharing revenue those chips eventually generate, rather than paying full cost upfront2
. This matters because site selection, power procurement, construction and hardware bring-up can take years before a startup runs a workload2
.Nvidia named Baseten, Fireworks AI and Together AI as examples of customers this revenue-sharing program is meant to serve—companies needing immediate, elastic access to AI cloud capacity for training, fine-tuning and high-volume inference without committing to years of hardware procurement
2
. The model represents a bet on the long tail of model builders, agent platforms and enterprises that want frontier compute capacity but not the balance-sheet risk of building a data center2
.Related Stories
The initiative gives Nvidia something it hasn't had at this scale before: a recurring, usage-linked income stream layered on top of hardware sales
2
. The company has already committed more than $40 billion to direct AI equity investments this year, spanning OpenAI, Nebius and dozens of smaller rounds2
. This revenue-sharing approach achieves similar goals without touching the cap table, keeping balance sheet exposure with cloud partners instead2
.The move illustrates the critical importance of access to scarce compute power for AI-oriented startups, with Nvidia GPUs likened to oil and reportedly tied to futures contracts as users grapple with fluctuations in cost and availability
1
. AI firms have increasingly entered revenue and equity-sharing agreements with chipmakers to circumvent liquidity issues. OpenAI has inked deals buying shares or entertaining investments from partners including Amazon and AMD, CNBC reported in January1
.If the model works, more compute reaches more startups faster than traditional buy-it-outright approaches allowed. However, if AI-native demand cools, Nvidia faces exposure to that slowdown twice—once through chip sales and again through the cloud revenue it has agreed to share
2
. Nvidia earlier this month said it was aiming to raise debt that sources indicated could amount to at least $20 billion for general corporate purposes1
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