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U.S. Department Of Energy·Tennessee

Financing Options for Supercomputer Hardware at Oak Ridge National Laboratory

Closes 2/20/2026$350M – $450MRequest for Information
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Description

The Oak Ridge National Laboratory (ORNL) is seeking information from qualified financial institutions, leasing providers, or other organizations capable of offering lease-to-own (LTO) financing for a leadership-class high-performance computing (HPC) supercomputer system named Discovery. The system will be sited at ORNL and is expected to have a total hardware value or financing amount of approximately $350M-$450M. The expected contract term is approximately 5 years, with fixed interest rates and monthly or quarterly payments. ORNL is seeking LTO financing options and plans to release a Request for Proposals (RFP) in late 2026. • The Discovery supercomputer system will be based on the HPE Cray Supercomputing GX5000, a next-generation supercomputer powered by AMD EPYC "Venice" processors and AMD Instinct MI430X GPUs. • The system will continue ORNL's and DOE's proven record of HPC leadership, supporting scientists in achieving cutting-edge breakthroughs and providing unprecedented computational science capabilities for the nation. • ORNL finances large HPC procurements with lease-to-own financing, as authorized by DOE Order 130.1A 4.a(13). • The RFI is issued solely for market research and planning purposes, and responses to this notice are not offers and cannot be accepted by UT-Battelle to form a binding contract.

Attached files

Contact

James Brimhall(Procurement Officer)

[email protected]

Key dates

Opened
1/16/2026
Closes
2/20/2026
Duration
5 years

Last updated

Details

Type
Request for Information
Industry
Information Technology and Software Development
NAICS
541519
Solicitation №
ACQFY26004

Budget estimate

$350,000,000 – $450,000,000

The budget for this opportunity is estimated to be in the range of $350M-$450M, which represents the total amount of principal to be financed for the lease-to-own financing of the Discovery supercomputer system. This estimate is based on the information provided in the RFI document and may be influenced by factors such as the terms and conditions of the lease agreement, the interest rate, and the payment schedule.

AI estimate from the solicitation

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