Lambda Secures $926 Million Investment-Grade Term Loan to Expand AI Cloud Infrastructure
SAN FRANCISCO — Lambda, the Superintelligence Cloud, announced that it has priced a $926 million senior secured Term Loan B facility to support the continued expansion of its GPU cloud platform and the deployment of infrastructure committed to customers.
The financing represents a significant milestone for Lambda and the broader AI infrastructure market. According to the company, the transaction is the first investment-grade-rated Term Loan B financing completed by a private neocloud, creating a new financing model for companies building large-scale AI computing infrastructure. The facility received a Baa2 rating from Moody’s, helping broaden the pool of institutional investors able to participate in AI infrastructure financing.
Lambda plans to use the proceeds to acquire and install GPU servers and related infrastructure required to deliver dedicated compute services to an investment-grade customer. The transaction attracted strong demand and was meaningfully oversubscribed, reflecting substantial institutional interest in AI infrastructure and Lambda’s contracted customer deployments.
Strong investor demand allowed Lambda and its financing partners to tighten pricing by 75 basis points from initial discussions. The facility was ultimately priced at SOFR plus 3.00% and issued at 99.5% of principal value.
The transaction is also Lambda’s first large-scale private cloud GPU asset-backed special purpose vehicle (SPV) financing. Through this structure, Lambda expects to establish a repeatable approach for financing committed customer deployments as it continues to expand its AI cloud platform.
Strengthening Lambda’s AI Infrastructure Financing Model
The new financing structure is designed to align the funding of GPU infrastructure with the contracted cash flows generated by customer deployments. This approach provides Lambda with additional flexibility as demand for high-performance computing continues to increase across AI training, inference, research, and enterprise applications.
The facility will be secured by the GPU servers and associated infrastructure acquired with the proceeds, as well as the contracted customer cash flows supporting those assets. The structure is intended to provide lenders with visibility into the underlying assets and associated revenue streams while enabling Lambda to continue scaling its infrastructure.
The financing carries a maturity date of December 31, 2030, with a fully amortizing repayment profile designed to align with the contracted cash flows and expected useful life of the underlying GPU infrastructure.
Facility Highlights
Key terms of the financing include:
- $926 million senior secured first-lien Term Loan B facility.
- Interest rate of SOFR plus 3.00%.
- Issued at 99.5% of principal amount.
- Maturity on December 31, 2030.
- Fully amortizing repayment structure.
- Secured by GPU servers and related infrastructure funded through the facility.
- Supported by contracted cash flows associated with the underlying customer deployments.
- Baa2 investment-grade rating from Moody’s.
Michel Combes, Chief Executive Officer of Lambda, said the transaction demonstrates growing institutional confidence in Lambda’s business model and the broader AI infrastructure sector.
“This transaction will establish Lambda as the first private neocloud to access the Term Loan B market with an investment-grade rating,” said Combes. “The significant pricing and investor interest we generated reflect the strength of our customer commitments, the quality of our infrastructure and growing institutional conviction in AI infrastructure as an asset class.”
The successful transaction comes as AI workloads continue to drive demand for large-scale GPU computing capacity. Organizations developing increasingly sophisticated AI models require access to substantial amounts of compute infrastructure, creating opportunities for specialized cloud providers such as Lambda.
Strong Institutional Investor Demand
The transaction received significant interest from a broad group of institutional investors and was meaningfully oversubscribed. The level of demand enabled the company to achieve more favorable pricing than initially anticipated.
The successful financing also demonstrates the potential for contracted GPU infrastructure to attract capital from traditional institutional credit markets. By connecting financing to dedicated infrastructure and contracted customer cash flows, Lambda is creating a model that could support additional investment in AI computing capacity.
Morgan Stanley served as lead left arranger, bookrunner, and administrative agent for the transaction, while MUFG served as joint bookrunner.
Davis Polk & Wardwell LLP acted as legal counsel to Lambda. Latham & Watkins LLP served as legal counsel to Morgan Stanley and the other arrangers.
The facility is expected to close in August 2026, subject to customary closing conditions.
Supporting the Growth of the Superintelligence Cloud
Lambda is focused on building and operating AI cloud infrastructure designed for both AI training and inference. The company serves a broad customer base that includes AI researchers, enterprises, and hyperscalers.
Founded in 2012 by machine learning engineers, Lambda develops and operates large-scale GPU computing systems designed to provide customers with access to high-performance AI infrastructure.
The company’s platform supports demanding AI workloads requiring substantial computational capacity. As organizations increasingly deploy generative AI, advanced machine learning, and other compute-intensive technologies, demand for scalable GPU infrastructure continues to expand.
Lambda describes its long-term mission as making compute as ubiquitous as electricity and giving individuals and organizations access to the capabilities of superintelligence.
The newly announced financing provides Lambda with additional capital to expand the physical infrastructure required to meet customer demand. By financing GPU deployments against contracted customer commitments, the company aims to create a scalable model for expanding its infrastructure while maintaining alignment between asset investment and customer cash flows.
Looking Ahead
The $926 million facility represents an important step in Lambda’s efforts to scale its AI cloud platform and develop new financing mechanisms for GPU infrastructure.
The investment-grade rating, strong institutional demand, and improved pricing demonstrate increasing recognition of AI infrastructure as an investable asset class. Lambda’s use of an asset-backed SPV structure also provides a framework that the company expects to leverage for future committed customer deployments.
As AI adoption expands across research, enterprise computing, and hyperscale environments, access to reliable GPU infrastructure is becoming increasingly important. Lambda intends to use the proceeds from the facility to accelerate the deployment of additional GPU servers and related systems, supporting its customers while expanding the capacity of its Superintelligence Cloud.
About Lambda
Lambda, the Superintelligence Cloud, is a provider of AI cloud infrastructure serving tens of thousands of customers. Founded in 2012 by published machine learning engineers, the company builds supercomputers designed for AI training and inference.
It’s customers range from individual AI researchers and enterprises to hyperscalers. The company’s mission is to make compute as ubiquitous as electricity and give everyone access to the power of superintelligence.
Forward-Looking Statements
This release contains forward-looking statements concerning It’s future activities, financing plans, infrastructure expansion, customer deployments, and expectations regarding the use of proceeds from the facility.
These statements reflect It’s current expectations and are subject to risks and uncertainties that could cause actual results to differ materially. Factors may include changes in market conditions, customer demand, financing availability, infrastructure deployment schedules, technology developments, and other factors beyond the company’s control.
Words such as “anticipate,” “believe,” “continue,” “expect,” “intend,” “plan,” and “will,” as well as similar expressions, are intended to identify forward-looking statements. It undertakes no obligation to update or revise these statements except as required by applicable law.
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