TL;DR · 30-second read
The Short Version
An Australian company called Sharon AI has borrowed 356 million US dollars and pledged the computer chips it is buying as security, much like a mortgage uses the house.
The chips are powerful Nvidia processors that run artificial intelligence. The loan costs about 10 percent a year, and Goldman Sachs is among the lenders.
The twist: lenders get repaid from what customers pay to rent those chips. So the loan really rests on Sharon AI’s customer deals, and it is only the first of several loans behind a plan to install 68,000 chips by mid-2027.
SharonAI Holdings Inc. (NASDAQ: SHAZ), an Australian provider of AI computing infrastructure, announced on October 1, 2026 that it has entered its first GPU-backed debt facility: a US$356 million committed, senior secured loan held in a special purpose vehicle and priced at a fixed 9.95%, excluding fees. The facility is secured against the GPUs and their associated cash flows, and proceeds will fund compute capacity dedicated to customer contracts.
Lenders include Goldman Sachs and select large private credit funds alongside Australian, Asian and global investors, with Jarden Australia acting as sole financial advisor and arranger. Sharon AI called it the first in an expected series of GPU financings supporting more than 68,000 NVIDIA GPUs deployed by mid-2027, and said it has now secured more than US$2.6 billion of debt and equity capital over ten months against a customer contract book worth more than US$8.8 billion.
Executive Summary
Sharon AI has opened a new funding channel for its GPU fleet: debt secured directly by the chips and the customer revenue they generate. The US$356 million facility is modest against the company’s 68,000-GPU build-out plan, but Sharon AI presents it as the template for a series of similar financings, shifting part of its hardware funding from equity to borrowed money at a fixed 9.95% rate before fees.
The significance lies in the structure. Because the security package combines hardware and contracted cash flows, the lenders are effectively underwriting Sharon AI’s customer contracts, with GPU resale value as the fallback. That makes the quality, length and enforceability of those contracts, rather than raw chip count, the variable that determines how much Sharon AI can borrow and at what price.
The deal also lands days after Sharon AI disclosed a change of auditor to Ernst & Young and announced a confidential-computing collaboration with VAST Data aimed at regulated customers, two developments that bear on how lenders and investors will judge the company’s reporting and its contract pipeline.
The Chip Is the Collateral, the Contract Is the Repayment
Sharon AI describes the facility as senior secured and GPU-backed, held in a special purpose vehicle (SPV), a separate legal entity set up to own specific assets and borrow against them. The security is “the GPUs and associated cash flows,” and proceeds will fund compute “dedicated to customer contracts.” Senior secured means these lenders are paid first and hold a direct claim on the pledged assets.
Put those pieces together and the lenders’ position becomes clear. In normal operation, the debt is serviced from what customers pay to use the specific GPUs inside the SPV. The chips themselves matter mainly if something goes wrong: if a customer stops paying or the SPV defaults, lenders can claim the hardware and its revenue stream. From the lender’s seat, each GPU is worth largely what its attached contract is expected to earn over the life of the loan, with resale value as the backstop.
That has consequences beyond Sharon AI’s balance sheet. Graphics processors are a fast-moving asset class, and each new NVIDIA generation can change what older chips fetch on the secondary market. A lender relying on resale value alone would carry that risk directly. Tying security to contracted cash flows moves the central credit question from what a chip will be worth at the end of the loan to whether the customer will keep paying, which makes the strength and duration of the customer book the main driver of how cheaply an AI cloud operator can finance hardware.
What a Fixed 9.95% Buys, and What It Leaves Out
The 9.95% rate is fixed, so Sharon AI’s interest bill will not rise if benchmark rates do, a useful match for revenue that comes from multi-year contracts at agreed prices. The figure explicitly excludes fees, however. Arrangement and commitment fees on structured facilities can be meaningful, so the all-in cost of this borrowing is higher than 9.95% by an amount the company has not stated.
Chief Executive James Manning said the structure is “designed to enhance return on equity.” The mechanism is simple: if the GPUs earn more than the cost of debt, borrowing lets shareholders keep the difference on a smaller equity base. The arithmetic also runs in reverse. If utilization, pricing or customer payments fall short, leverage magnifies losses for equity holders, who rank behind senior lenders. Whether the claim holds depends on contract economics Sharon AI has not published.
The lender roster adds context. Goldman Sachs and “select large private credit funds” sit alongside Australian and Asian investors. Private credit, meaning lending by investment funds rather than banks, commonly provides asset-backed loans of this kind, and a committed facility (money promised up to a limit) gives Sharon AI drawable capacity as deployments come online.
$356 Million Is the Opening Tranche of a 68,000-GPU Plan
Sharon AI calls the facility “the first in an expected series of GPU financings” behind a scheduled build-out of more than 68,000 NVIDIA GPUs by mid-2027. It has not said how many of those chips this US$356 million covers, but the framing is clear: this is a repeatable structure, not the whole bill.
Two company figures set the scale. Sharon AI says it has secured more than US$2.6 billion of institutional debt and equity over the past ten months, and that its customer offtake, meaning contracted commitments to buy compute, stands at a total contract value (TCV) above US$8.8 billion. TCV sums the full value of contracts across their entire terms, so it is not annual revenue, and its worth to a lender depends on contract length, cancellation rights and counterparty strength. Sharon AI lists hyperscalers (the largest cloud platforms), AI-native companies, government, enterprise and research organizations among its customers, without naming those behind this facility.
The company is also building product features for regulated buyers. On September 23 it announced a collaboration with VAST Data to offer VAST DataEnclave, a confidential-computing environment in which, the companies say, customer data and model weights remain encrypted even from Sharon AI as operator, targeting banks, government agencies and other regulated organizations. If such features help win long-dated contracts from institutional customers, they feed directly into the cash flows that secure facilities like this one.
Reporting Discipline Matters More Once Debt Is Layered In
Lenders monitor borrowers through their financial reporting, so audit quality becomes more important as debt is added. In an 8-K filed September 24, Sharon AI disclosed that its Audit Committee approved ending HoganTaylor LLP’s engagement on September 20 and engaged Ernst & Young on September 23 for the fiscal 2026 audit, following a competitive process involving several firms.
The filing states there were no disagreements with HoganTaylor and that its audit reports for 2024 and 2025 carried no adverse or qualified opinions. It does list one reportable event: a material weakness, meaning a significant gap in internal controls over financial reporting, identified by HoganTaylor and disclosed in the 10-K filed March 31, 2026. Moving to a Big Four auditor is a common step for a growing public company, and the filing gives no indication of a dispute. It does not say whether the material weakness has been remediated, and for a borrower planning a series of GPU-backed facilities, reliable controls over cash flows and asset records are part of what lenders are underwriting.
Background
SharonAI Holdings Inc. trades on Nasdaq under the ticker SHAZ and describes itself as an Australian “neocloud,” a specialist provider that rents GPU computing power for AI rather than offering general-purpose cloud services. Through its AI Factory platform and a network of technology and co-location partners (data center operators that host its equipment), it serves organizations training and running AI models, with an emphasis on sovereign infrastructure that keeps data within national borders. It reports to the SEC as an emerging growth company.
Companies in this segment typically need large sums up front to buy GPUs before customer revenue arrives, which makes financing structure central to their growth. Sharon AI says its ambition is gigawatt-scale compute capacity across Australia, New Zealand and the broader Asia-Pacific, a gigawatt being roughly the output of a large power station. Source: Sharon AI Enters Into GPU-Backed Debt Facility, Expanding Funding Flexibility for AI Factory Deployments, Sharon AI’s announcement of its US$356 million GPU-backed SPV debt facility. Primary sources: SharonAI Holdings 8-K filed September 24, 2026 (change in certifying accountant); SharonAI Holdings 8-K/A filed September 23, 2026; Exhibit 99.1 to 8-K/A: Sharon AI Collaborates with VAST Data on the Launch of DataEnclave; SharonAI Holdings 8-K filed September 23, 2026; Exhibit 99.1 to 8-K: Sharon AI Collaborates with VAST Data on the Launch of DataEnclave.Sources