AI models
Re-Dock
Training compute
7.5×10¹⁹ FLOP
Published
Feb 21, 2024
Re-Dock is an AI model developed by Zhejiang University (ZJU), Westlake University and University of Washington (China and United States), first published in February 2024. It works in the biology domain, on tasks such as protein-ligand contact prediction.
Training it took an estimated 7.5×10¹⁹ FLOP of compute (estimation method: hardware). Training ran on 1 NVIDIA A100 for about 168 hours.
The reference paper has 24 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Zhejiang University (ZJU), Westlake University, University of Washington
- Country of organization
- China, United States
- Domain
- Biology
- Task
- Protein-ligand contact prediction
- Training compute
- 7.5×10¹⁹ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA A100
- Chips used
- 1
- Training time
- 168 h
- Training power draw
- 435 W
- Citations
- 24
- 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.
← All ai models