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"CZI Accelerating and Scaling Biological Sciences via AI Request for Applications for GPU Compute Allocations" is currently closed and not accepting applications.
The Chan Zuckerberg Initiative (CZI) invites proposals to build large-scale AI and machine learning models for the biological sciences through competitive allocations on CZI's GPU cluster of 1,024 NVIDIA H100 GPUs in an NVIDIA DGX SuperPOD configuration with VAST fast data storage. The program targets foundation model development for biology, virtual cells, and disease research.
Priority is given to projects aligned with CZI's Virtual Cell initiative and the broader mission to cure, prevent, or manage all diseases by the end of the century. The cluster is optimized for AI/ML training at scale, with applications evaluated on rolling deadlines until full cluster allocation is reached.
Recipients receive a minimum allocation of 96 GPUs as an in-kind award, enabling training of foundation models that would otherwise be financially prohibitive through conventional university resources. Approved projects integrate with CZI's growing virtual cell ecosystem alongside partner institutions including the Broad Institute, Allen Institute, Arc Institute, and Wellcome Sanger Institute.
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Or search similar grants →According to the current listing, eligibility includes: Principal Investigators and Co-PIs must hold faculty or equivalent independent investigator status at U.S.-based nonprofit institutions including colleges, universities, hospitals, independent research labs, and government agencies. For-profit entities are ineligible. Meta employees are prohibited from applying. Applicants must commit to using minimum 96 GPU utilization during training phases and align with CZI's biomedical mission. Strong preference for projects building foundation models, virtual cell models, or large-scale AI systems advancing biological discovery. Confirm the full requirements in the official notice before applying.
The current listing shows in-kind GPU compute allocation on CZI's cluster of 1,024 NVIDIA H100 GPUs in a DGX SuperPOD configuration. Minimum allocation of 96 GPUs per project for training large-scale biological AI models. No cash funds awarded; the in-kind value of allocations ranges from approximately $250,000 to several million USD depending on GPU-hour usage and project duration. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was June 18, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
CZI Accelerating and Scaling Biological Sciences via AI Request for Applications for GPU Compute Allocations is funded by Chan Zuckerberg Initiative (CZI). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.