AI models
Uni-Mol Molecular Model
Training compute
5.4×10¹⁸ FLOP
Published
Mar 6, 2023
Uni-Mol Molecular Model is an AI model developed by Renmin University of China, DP Technology, AI for Science Institute and Beijing (AISI) (China), first published in March 2023. It works in the biology domain, on tasks such as molecular representation learning, molecular property prediction, protein-ligand contact prediction and drug discovery.
Training it took an estimated 5.4×10¹⁸ FLOP of compute (estimation method: hardware). Training ran on 8 NVIDIA Tesla V100 DGXS 32 GB for about 20 hours.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Renmin University of China, DP Technology, AI for Science Institute, Beijing (AISI)
- Country of organization
- China
- Domain
- Biology
- Task
- Molecular representation learning, Molecular property prediction, Protein-ligand contact prediction, Drug discovery
- Training compute
- 5.4×10¹⁸ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA Tesla V100 DGXS 32 GB
- Chips used
- 8
- Training time
- 20 h
- Training power draw
- 4.0 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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