AI models
GemNet-OC
Training compute
5.4×10²⁰ FLOP
Published
Sep 30, 2022
GemNet-OC is an AI model developed by Technical University of Munich, Carnegie Mellon University (CMU) and Facebook AI Research (Germany, United States and France), first published in September 2022. It works in the materials science domain, on tasks such as molecular simulation, molecular property prediction, atomistic simulations and 2 more.
Training it took an estimated 5.4×10²⁰ FLOP of compute (estimation method: hardware). Training ran on NVIDIA V100.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Technical University of Munich, Carnegie Mellon University (CMU), Facebook AI Research
- Country of organization
- Germany, United States, France
- Domain
- Materials science
- Task
- Molecular simulation, Molecular property prediction, Atomistic simulations, Molecular representation learning, Materials design
- Training compute
- 5.4×10²⁰ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA V100
- Chip-hours
- 4K
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Epoch confidence
- Likely
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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