AI models
MACE-MP-0
Training compute
8.8×10²⁰ FLOP
Published
Mar 1, 2024
MACE-MP-0 is an AI model developed by University of Cambridge, Federal Institute of Materials Research and Testing (BAM), NERSC, Lawrence Berkeley National Laboratory, University of British Columbia (UBC), Friedrich Schiller University Jena and 16 more (United Kingdom, Germany, United States, Canada and 3 more), first published in March 2024. It works in the materials science domain, on tasks such as molecular simulation.
Training it took an estimated 8.8×10²⁰ FLOP of compute (estimation method: hardware). Training ran on 80 NVIDIA A100.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- University of Cambridge, Federal Institute of Materials Research and Testing (BAM), NERSC, Lawrence Berkeley National Laboratory, University of British Columbia (UBC), Friedrich Schiller University Jena, University of Bayreuth, Fritz Haber Institute of the Max Planck Society, U. S. Naval Research Laboratory, Chemix, Daresbury Laboratory, BASF, University of South Carolina, University of Stuttgart, Uppsala University, Newcastle University, Technical University of Denmark, Aix-Marseille Université, University of Warwick, University of California Los Angeles (UCLA), InstaDeep, University of California (UC) Berkeley
- Country of organization
- United Kingdom, Germany, United States, Canada, Sweden, Denmark, France
- Domain
- Materials science
- Task
- Molecular simulation
- Training compute
- 8.8×10²⁰ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA A100
- Chips used
- 80
- Chip-hours
- 2.6K
- Training power draw
- 63.3 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- 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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