AI models
FourCastNet
Training compute
3.5×10²⁰ FLOP
Published
Feb 22, 2022
FourCastNet is an AI model developed by NVIDIA, NERSC, Lawrence Berkeley National Laboratory, University of Michigan, Rice University, California Institute of Technology and Purdue University (United States), first published in February 2022. It works in the earth science domain, on tasks such as weather forecasting.
Training it took an estimated 3.5×10²⁰ FLOP of compute (estimation method: hardware). Training ran on 64 NVIDIA A100 for about 16 hours.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- NVIDIA, NERSC, Lawrence Berkeley National Laboratory, University of Michigan, Rice University, California Institute of Technology, Purdue University
- Country of organization
- United States
- Domain
- Earth science
- Task
- Weather forecasting
- Training compute
- 3.5×10²⁰ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA A100
- Chips used
- 64
- Training time
- 16 h
- Training power draw
- 51.5 kW
- Model accessibility
- Unreleased
- Open weights
- No
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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