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CZI's Accelerating and Scaling Biological Sciences with AI RFA awards compute, not money, and that distinction shapes everything about who should apply. Successful projects receive an allocation on CZI's cluster of 1,024 NVIDIA H100 GPUs in an NVIDIA DGX SuperPOD configuration; the RFA is explicit that there are no cash funds, financial contributions or fees of any kind.
Salaries, data acquisition and everything else must already be funded. The floor is a real filter: projects must use a minimum of 96 GPUs during their large training phase, which excludes ordinary fine-tuning work and targets teams genuinely training large-scale AI and machine learning models for the biological sciences.
Priority goes to virtual cell modelling, consistent with CZI's mission to cure, prevent or manage all diseases by the end of the century. Allocations run for a maximum of one year from project start. Two conditions deserve attention before applying.
First, open science is mandatory - code and model weights must be shared - so teams with commercial or embargo constraints should not apply. Second, only de-identified data may be used, and institutional sign-off is required.
Eligibility is restricted to U.S.-based domestic nonprofit organisations including colleges, universities, hospitals, research labs and government agencies; for-profit organisations are ineligible, PIs and Co-PIs must hold faculty or equivalent independent investigator status at a U.S. nonprofit institution, and Meta employees are ineligible.
Review is on a rolling basis against periodic review dates, with the practical warning that the cluster may reach full allocation before the final deadline of a cycle - applying early in a cycle materially improves the odds. Applicants should confirm current cycle dates with CZI at sciencegrants@chanzuckerberg. com.
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Or search similar grants →According to the current listing, eligibility includes: Eligibility is limited to U.S.-based domestic nonprofit organisations, including colleges, universities, hospitals, research labs and government agencies; for-profit organisations are ineligible. Principal Investigators and Co-PIs must hold faculty or equivalent independent investigator status at a U.S. nonprofit institution, and Meta employees are ineligible. Projects must use a minimum of 96 GPUs during their large training phase, which is a hard technical eligibility threshold rather than a preference, and are limited to a maximum project period of one year from start. The award is an in-kind allocation on CZI's cluster of 1,024 NVIDIA H100 GPUs in an NVIDIA DGX SuperPOD configuration and provides no cash funds, financial contributions or fees of any kind, so personnel, data and other project costs must be funded from elsewhere. Scope is large-scale AI and machine learning model development for the biological sciences, with priority given to virtual cell modelling aligned with CZI's mission to cure, prevent or manage all diseases by the end of the century. Awardees must commit to open science, including mandatory sharing of code and model weights, may use only de-identified data, and require institutional sign-off. Applications are reviewed on a rolling basis against periodic review dates and the cluster may reach full allocation before a cycle's final deadline, so early submission is advantageous. Prospective applicants should confirm the current cycle's portal opening and review dates directly with CZI at sciencegrants@chanzuckerberg.com. Confirm the full requirements in the official notice before applying.
The current listing shows this award is entirely in-kind: it grants allocation on CZI's high-performance computing cluster of 1,024 NVIDIA H100 GPUs and provides no cash funds, financial contributions or fees of any kind. Because no monetary award is made, amount_min and amount_max are both recorded as 0. The meaningful award size is measured in GPUs rather than dollars - projects must use a minimum of 96 GPUs during their large training phase, and no maximum allocation is published. Applicants budgeting for personnel, data or publication costs must secure those funds elsewhere. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Chan Zuckerberg Initiative Accelerating and Scaling Biological Sciences with AI RFA for Allocations on the CZI 1,024 NVIDIA H100 GPU Cluster 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.