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This Subcontract opportunity from Department Of Defense was posted on July 13, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Performance Evaluation & Benchmarking of Multiscale Systems

Closed
Federal

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This subcontract, issued by the Defense Advanced Research Projects Agency under the Department of Defense, focuses on the performance evaluation and benchmarking of multiscale systems. The primary objective is to design and implement comprehensive evaluation frameworks capable of assessing multiscale reasoning systems across several critical dimensions, including cross-scale prediction accuracy, forecast horizons, and the prediction of interventions. Additionally, the scope of work requires the assessment of mechanistic fidelity and the ability of these systems to remain robust when dealing with sparse data. Interested parties must submit their responses by August 10, 2026, in accordance with the solicitation posted on July 13, 2026, under NAICS code 541690.

General Info

DARPA subcontract for benchmarking multiscale reasoning systems; responses due by August 10, 2026.

NAICS

541690 - Other Scientific and Technical Consulting Services

Place of Performance

VA

Set-Aside

NONE

Documents

This scope was carved out of DARPA-SN-26-100.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Multiscale Reasoning For Human Physiology RFI

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyDepartment Of Defense → Defense Advanced Research Projects Agcy
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Design and implement evaluation frameworks to assess multiscale reasoning systems on cross-scale prediction accuracy, forecast horizon, intervention prediction, mechanistic fidelity, and robustness to sparse data.

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