This Combined Synopsis/Solicitation opportunity from Department Of Defense was posted on May 5, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.
GPU Compute Servies for Network of Optimal Dynamic Energy Signatures
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The Defense Advanced Research Projects Agency is seeking a managed high-performance computing solution to support the Network of Optimal Dynamic Energy Signatures program, which requires robust GPU-based compute, high-speed networking, and secure data storage to enable large-scale biological data analysis and computational modeling. The solicitation, numbered HR001126QE003, seeks a firm-fixed-price contract for 50 baseline NVIDIA HGX H100 80GB SXM5 GPUs or equivalent or superior alternatives such as the Blackwell B200/GB200, along with 100 reserve GPUs, 550TB of NFS storage, and NVLink/InfiniBand interconnects, all to be fully operational by May 15, 2026, with performance extending through March 14, 2027. The solution must be hosted exclusively within the United States or its territories, with any non-U.S. infrastructure subject to rigorous justification and risk assessment, and must maintain SOC 2 Type II compliance—ISO 27001 is not an acceptable substitute. The contract includes three CLINs: CLIN 0001 for base period GPU-hour usage, CLIN 0002 for the optional period, and CLIN 0003 for ancillary costs priced at a firm-fixed rate, with pricing evaluated on a per-GPU-hour basis using estimated totals of 183,600 and 181,200 hours respectively. The evaluation is a best-value trade-off, where technical approach and past performance are significantly more important than price, and failure to meet any mandatory requirement—such as GPU availability by the deadline, valid SOC 2 certification, or non-use of adversarial nation data centers—results in automatic disqualification. Proposals must be structured into three volumes: Technical (maximum 10 pages, no pricing), Price (unrestricted), and Administrative (including UEI, CAGE Code, and SF 1449), with all submissions due electronically to NODES@darpa.mil by May 8, 2026, following an amendment that extended the original deadline. The technical specification allows for GPU alternatives if proven superior, and contractors may propose migration plans to future hardware, though any material change requires formal contract modification. Security is paramount, with explicit prohibition on data center hosting in adversarial nations, and contractors relying on subcontractor SOC 2 certifications must affirm
General Info
Agency
NAICS
Place of Performance
Arlington, VA, USASet-Aside
Timeline
Submission Closed
Organization & Contact Information
Full Description
Amendment 0002: The purpose of this amendment is to extend the quote due date, provide Government responses to questions, incorporate the resulting revisions into the technical specifications, instructions, and evaluation criteria, revise CLIN description, and insert FAR Clause 52.222-90.
Amendment 0001: The purpose of Amendment 0001 is to The purpose of amendment one is to: (1) Add CLIN 0003; (2) Modify CLIN 0001 and CLIN 0002; (3) Update Attachment 1 "Technical Specifications Document", Attachment 2 "Section L- Instructions, Conditions, and Notices to Quoters," and Attachment 3 "Section M -Evaluation Factors for Award; and (4) Post Questions and Answers.
The Defense Advanced Research Projects Agency is seeking a dedicated, managed high-performance computing (HPC) solution that includes compute hardware, network-attached storage, high-speed networking, robust security controls, and comprehensive user support. The solution must meet the performance, availability, and security standards detailed herein to support the Network of Optimal Dynamic Energy Signatures (NODES) program's scientific objectives. The NODES program seeks to enable distributed, data-driven biological discovery by integrating experimental platforms, large-scale biological datasets, and advanced computational methods. NODES performers generate and analyze substantial volumes of heterogeneous biological data and rely on computational workflows to enable rapid hypothesis generation, model development, and validation across a networked ecosystem.
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