Funding

Nscale Closes $3B in Term Loans

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Nscale has closed approximately $3 billion in aggregate commitments across two senior secured delayed draw term loan facilities backing a pair of U.S. AI infrastructure projects, the London-based company announced on August 31, 2026. One facility supports its Ward County, Texas campus and the other its Madison, North Carolina site, and Nscale said both facilities received investment-grade ratings with stable outlooks.

The Ward County facility provides up to $1.85 billion, issued through Nscale Ward County Borrower SPV, LLC. The Madison facility provides up to $1.2 billion. According to the company, the facilities will primarily fund the deployment of GPU infrastructure along with associated networking, storage, and liquid-cooling equipment across both campuses.

Ward County, Texas

Nscale describes the Ward County campus as a purpose-built AI infrastructure site designed for high-density, next-generation compute deployments. The facility combines closed-loop direct liquid cooling with rear-door heat exchangers, a pairing the company says enables efficient operation of advanced AI systems at scale.

The up to $1.85 billion loan will fund the deployment of NVIDIA GB300 (Blackwell Ultra) and VR200 (Vera Rubin) systems supporting approximately 275 MW of IT load. That capacity places the Texas campus among the larger single-site GPU deployments Nscale has detailed to date, and the hardware mix spans two successive generations of NVIDIA data center platforms.

Madison, North Carolina

The second facility finances a different kind of build. The Madison site is a 96-acre colocation property with up to 40 MW of capacity. Nscale said the up to $1.2 billion loan will fund site retrofit capital expenditures, GPU infrastructure, and the associated networking required to support high-performance AI compute deployments.

Unlike the greenfield Texas campus, the North Carolina project centers on retrofitting an existing colocation site, with the debt package covering both the physical upgrade work and the compute hardware going into it.

Financing Structure and Arrangers

Both facilities are structured as senior secured delayed draw term loans, an arrangement that lets the borrower draw capital over time as deployment milestones are funded rather than taking the full commitment upfront. The Ward County borrowing runs through a dedicated special-purpose vehicle, Nscale Ward County Borrower SPV, LLC.

J.P. Morgan and Goldman Sachs served as joint lead arrangers, joint bookrunners, and co-structuring agents for both facilities. J.P. Morgan served as lead left arranger on the Ward County facility, while Goldman Sachs served as lead left arranger on the North Carolina facility.

Earlier Debt and Equity Raises

The two closings extend a run of financing activity at Nscale through 2026. On July 7, 2026, the company closed a $900 million revolving credit facility providing liquidity for its AI data center build-out and capital deployment across the US, Europe, and APAC. That facility was syndicated across J.P. Morgan, Goldman Sachs, Morgan Stanley, MUFG, RBC Capital Markets, Bank of America, Crédit Agricole CIB, Deutsche Bank, Mizuho, SMBC, TD Securities, and KeyBank N.A.

Earlier, on February 12, 2026, Nscale signed a $1.4 billion delayed draw term loan backed by GPUs to finance cluster deployments in Norway, Portugal, Iceland, and the UK. That loan was led by funds managed by PIMCO, Blue Owl, and LuminArx Capital Management, with Goldman Sachs acting as sole structuring agent and sole placement agent. At the time, the company said that raise followed its $1.1 billion Series B equity round and a $433 million Pre-Series C SAFE.

Nscale describes itself as a full-stack AI cloud platform, combining a unified cloud platform for AI training and inference with the data centers and power supply behind it. Headquartered in Europe and operating globally, the company delivers compute, networking, storage, managed software, and AI services in Nscale-owned and colocated data centers.

Theo Nash is an AI-generated specialist at Unite.AI, covering AI infrastructure, compute, and the hardware systems that power modern artificial intelligence. His work focuses on the technical foundations behind large-scale AI workloads, including data centers, accelerators, networking, and the software stacks that tie them together.

With an analytical and engineering-driven perspective, Theo examines how advances in GPUs, custom silicon, memory architectures, and distributed systems enable new generations of AI models. He pays particular attention to performance trade-offs, energy efficiency, scalability, and the practical constraints that shape real-world deployment of AI infrastructure.

Articles authored by Theo Nash are AI-generated and reviewed by Unite.AI’s editorial team to ensure technical accuracy, clarity, and responsible coverage of the rapidly evolving AI compute landscape.