Nvidia Pledges $125B Backstop to Unlock $500B in AI Financing

Anderseidesvik · CC BY-SA 4.0 (via Wikimedia Commons)
The Core · TL;DR
- Nvidia signed MOUs with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to raise over $500B in third-party AI infrastructure financing.
- Nvidia will guarantee up to 25% of GPU residual value as collateral backstop, potentially totaling $125 billion per Jensen Huang.
- BlackRock's Larry Fink compared the plan to the 1970s emergence of mortgage-backed securities as chips become a new asset class.
- Nvidia shares fell about 1.4%, wiping out over $70 billion in market cap, despite the deal's scale.
Nvidia has signed memoranda of understanding with six of Wall Street's largest asset managers to mobilize more than $500 billion in outside capital for AI infrastructure. Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR are the partners named in the plan.
The money is meant to fund data centers, chip fabrication plants, and the power generation needed to run them. Nvidia CEO Jensen Huang framed the effort as a move away from financing AI buildouts project by project, toward standing platforms that can be repeated at scale.
The mechanism hinges on Nvidia's own balance sheet. The company is guaranteeing up to 25 percent of the residual value of GPUs pledged as collateral, meaning that if the chips underperform their expected resale value, Nvidia covers a share of the gap.
Huang has said Nvidia could ultimately be on the hook for as much as $125 billion, a quarter of the overall $500 billion target. Importantly, that figure is not new revenue or a single fund. It is an aggregate goal spread across years and multiple deals, and it is not tied to any one customer.
Turning GPUs into an asset class
The deals are structured as MOUs rather than binding contracts, leaving room for terms to shift before capital actually moves. Goldman Sachs is separately exploring a market for credit instruments backed directly by Nvidia compute capacity.
BlackRock CEO Larry Fink drew a comparison to the birth of mortgage-backed securities in the 1970s, when banks began bundling loans into tradable assets. Blackstone President Jon Gray echoed that framing, likening the valuation approach to how lenders assess housing collateral.
Huang has said he personally approached the financial firms with the idea, according to Goldman Sachs CEO David Solomon.
The plan leans on data suggesting GPUs hold value longer than skeptics assume. Nvidia points to its 2020-era A100 chip, still in commercial use six years on, with contract rates for the newer H100 rising from $1.70 to $2.35 per GPU-hour between October 2025 and March 2026.
Nvidia has already committed billions to customers such as OpenAI and Anthropic, along with neocloud operators CoreWeave, Nebius, Firmus, and Lambda. Those relationships sit against a backdrop in which Big Tech's collective AI spending is projected to exceed $730 billion this year, according to Reuters.
Markets did not universally cheer the news. Nvidia's stock fell roughly 1.4 percent following the announcement, erasing more than $70 billion in market capitalization, a reminder that guaranteeing chip value also concentrates risk back onto the guarantor.
Original reporting and research used to synthesize this article.
- 1Nvidia targets USD 500 bn in third-party financing to fuel AI data center boomenterpriseam.com
- 2Nvidia’s new $500B plan is risky but brilliant, especially for aging GPUstechcrunch.com
- 3Nvidia guarantees its own chips' value to unlock $500 billion in AI infrastructure financingthe-decoder.com
- 4Nvidia Partners With Wall Street Giants on $500B Push to Turn AI Chips Into New Asset Classtheaiinsider.tech
WAKIB Editorial Team
This review was prepared and summarized by the WAKIB AI intelligence engine and vetted by our editorial board for accuracy and reliability.
Subscribe to Newsletter
Get a weekly summary of the most promising AI research and tools delivered to your inbox.
Telegram Channel
Join our active community on Telegram for real-time tracking of AI models and trends.
