1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
This listing may be outdated. Verify details at the official source before applying.
Find similar grantsNVIDIA Corporation matches donations from employees to eligible nonprofits. This program amplifies personal donations of time and money from NVIDIA employees.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →According to the current listing, eligibility includes: Nonprofit organizations recognized as 501(c)(3) organizations (for U. S. organizations) that receive donations from eligible NVIDIA employees (full-time, part-time, and interns). Confirm the full requirements in the official notice before applying.
The current listing shows up to $10,000 per employee annually. Verify award ceilings, matching requirements, and allowable costs in the official notice.
NVIDIA Foundation Matching Gift Program is funded by NVIDIA Foundation. 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.
Past winners and funding trends for this program
ERCAP (Energy Research Computing Allocations Process) allocates compute time on NERSC's Perlmutter supercomputer at Lawrence Berkeley National Laboratory, one of the world's largest GPU-based systems with over 7,000 NVIDIA A100 GPUs alongside AMD EPYC CPUs. ERCAP is the primary mechanism for the broader DOE Office of Science research community (and partner researchers) to access leadership-class GPU resources for AI/ML, foundation model training, scientific AI, climate AI, materials AI, and AI-coupled simulation. Annual allocation cycle: submissions typically open in August and close in early October, with allocations starting January 1 of the following year. The 2026-cycle ERCAP call closed October 8, 2026 for 2027 allocations. NERSC supports both pre-trained foundation model fine-tuning and pre-training campaigns, with a growing AI/ML user community. Recipients receive both compute hours and consultation from NERSC's NESAP for AI program providing hands-on optimization, MLOps support, and access to advanced features (interactive nodes, Jupyter at scale, ML-optimized storage). ERCAP complements DOE's INCITE (largest) and ALCC (mission-aligned) allocation pathways.
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.
Google Cloud's startup program provides substantial cloud computing credits specifically designed for AI and ML companies. The program offers access to cutting-edge GPU and TPU hardware including NVIDIA H100, A3 Ultra instances, and TPU v5e accelerators. Credits can be used for AI model training, inference, data processing, and general cloud infrastructure. The tiered program scales credits based on company stage and backing, making it one of the largest compute credit programs available for AI startups building on foundation models, computer vision, NLP, and other AI applications.
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.
Read article