AI models
GraSR
Training compute
3.8×10¹⁸ FLOP
Published
Mar 24, 2022
GraSR is an AI model developed by Shanghai Jiao Tong University and Ministry of Education of China (China), first published in March 2022. It works in the biology domain, on tasks such as protein structure comparison.
Training it took an estimated 3.8×10¹⁸ FLOP of compute (estimation method: hardware). It was trained on roughly 13.3K datapoints. Training ran on 2 NVIDIA TITAN Xp for about 120 hours.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 28 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Shanghai Jiao Tong University, Ministry of Education of China
- Country of organization
- China
- Domain
- Biology
- Task
- Protein structure comparison
- Training compute
- 3.8×10¹⁸ FLOP
- Compute estimation method
- Hardware
- Dataset size
- 13.3K
- Training hardware
- NVIDIA TITAN Xp
- Chips used
- 2
- Training time
- 120 h
- Training power draw
- 1.0 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 28
- 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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