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Find similar grantsNVIDIA's Academic Grant Program has an open call for research proposals focused on generative AI training and model development, including foundation models for scientific domains and techniques for training, scaling, and customizing.
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Or search similar grants →According to the current listing, eligibility includes: Full-time faculty members at accredited academic institutions. One proposal per faculty or research group, per quarter. Confirm the full requirements in the official notice before applying.
The current listing shows compute resources (DGX Spark, RTX PRO 6000 Blackwell, A100 GPU hours). Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was June 30, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
NVIDIA Academic Grant Program - Generative AI training and model development is funded by NVIDIA. Verify program details on the funder's official page before applying.
This listing is flagged as international in scope. Check the official notice for country-specific restrictions before applying.
Applications go through the funder's official portal — the Apply Now link on this page goes there directly.
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NVIDIA's Academic Hardware Grant Program donates GPU hardware to qualifying academic researchers, with a specific track focused on AI Safety and Trustworthy AI research (including interpretability, alignment, evaluation, red-teaming, and bias/fairness). Awardees receive workstation- or datacenter-class NVIDIA GPUs delivered to their institutions for use in research projects. Applications are accepted on a rolling basis through the NVIDIA Higher Education and Research portal. Projects must produce a publishable research output or open-source artifact and acknowledge NVIDIA's hardware contribution. The AI Safety track is specifically highlighted by NVIDIA's collaboration with the AI Safety Directory and prioritizes researchers working on interpretability, evaluations, robustness, and trustworthy ML. Strong fit for graduate students, postdocs, and early-career faculty doing AI safety, alignment, or interpretability research at universities without existing GPU access, as well as nonprofit AI safety research organizations.
NVIDIA's Applied Research Accelerator Program provides academic researchers with GPU hardware, cloud compute, and cash support in three tiers: Base ($20K for projects with real-world impact potential), Adoption ($60K for projects with commercial or government adoption plans), and Production ($160K when organizations invest in production conversion). The program supports research with practical applications in GPU-accelerated computing, AI, machine learning, data analytics, and HPC. Applications are reviewed quarterly with four annual cycles: Q1 submissions decided June, Q2 decided September, Q3 decided December, Q4 decided March.
NSF ACCESS (Advanced Cyberinfrastructure Coordination Ecosystem: Services and Support) provides access to dozens of high-performance computing systems including GPU clusters at no cost for academic research and education. The program replaced XSEDE in 2022 and offers tiered allocation levels from small-scale pilot experiments to large-scale research campaigns. Recent hardware upgrades through the NAIRR Pilot added NVIDIA H100 GPUs at multiple sites. Particularly valuable for AI/ML researchers needing GPU time for model training, inference, and large-scale experiments without existing funding.
The Polyphonic AI Fund for Surgery QuickFire Challenge, launched by Johnson & Johnson MedTech in partnership with NVIDIA and AWS, invites researchers and innovators worldwide to submit AI technologies that improve surgical outcomes. The challenge focuses on three areas: surgical decision support (perioperative AI that augments care delivery and serves as a surgeon co-pilot), data management and governance (breakthroughs in data infrastructure, privacy, and consent management for surgical data), and surgical efficiency (boosting coordination across care teams and improving patient management). Awardees receive up to $100,000 in grant funding plus mentorship from J&J experts, access to GPUs and accelerated computing resources from NVIDIA, and cloud services from AWS. The second cohort is currently accepting applications with quarterly award announcements through end of 2026. This is one of the few corporate-backed AI grants specifically targeting surgical robotics and operating room AI innovation.
The Digital Research Alliance of Canada's Accelerated AI Investments program deploys up to $40 million in the 2025-2026 fiscal year to provide dedicated AI compute resources for Canadian researchers. The initiative makes GPU clusters including NVIDIA H100 and A100 hardware available through national HPC facilities including Narval, Cedar, Graham, and Niagara. Resources support AI model training, large language model fine-tuning, computer vision research, and other compute-intensive AI workloads. The program is part of Canada's broader Pan-Canadian AI Strategy which has invested over $2 billion since its launch. Allocations are processed through the Alliance's Resource Allocation Competition (RAC) and Rapid Access Service (RAS) pathways.
NSF 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleThe OMAI project — led by AI2, funded by NSF and NVIDIA — will create fully open multimodal AI models for scientific research. For researchers priced out of commercial AI, this changes the equation.
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