AI models
Prithvi WxC
Training compute
7.2×10¹⁹ FLOP
Parameters
2.3B
Published
Sep 20, 2024
Prithvi WxC is an AI model developed by IBM Research, University of Alabama, Stanford University, Colorado State University, Oak Ridge National Laboratory and NASA (United States), first published in September 2024. It works in the earth science domain, on tasks such as weather forecasting.
Training it took an estimated 7.2×10¹⁹ FLOP of compute (estimation method: operation counting). The model has 2,300,000,000 parameters. Training ran on 64 NVIDIA A100.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 38 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- IBM Research, University of Alabama, Stanford University, Colorado State University, Oak Ridge National Laboratory, NASA
- Country of organization
- United States
- Domain
- Earth science
- Task
- Weather forecasting
- Training compute
- 7.2×10¹⁹ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 2,300,000,000
- Training hardware
- NVIDIA A100
- Chips used
- 64
- Training power draw
- 50.4 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 38
- 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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