AI models
AlphaFold 3
Training compute
4.1×10²² FLOP
Published
May 8, 2024
AlphaFold 3 is an AI model developed by Google DeepMind and Isomorphic Labs (United States and United Kingdom), first published in May 2024. It works in the biology domain, on tasks such as protein folding prediction, antibody property prediction, protein-ligand contact prediction and 2 more.
Training it took an estimated 4.1×10²² FLOP of compute (estimation method: hardware). It was trained on roughly 29.5B datapoints. Training ran on 256 NVIDIA A100 for about 480 hours.
Access: Open weights (non-commercial). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Google DeepMind, Isomorphic Labs
- Country of organization
- United States, United Kingdom
- Domain
- Biology
- Task
- Protein folding prediction, Antibody property prediction, Protein-ligand contact prediction, RNA structure prediction, Protein interaction prediction
- Training compute
- 4.1×10²² FLOP
- Compute estimation method
- Hardware
- Dataset size
- 29.5B
- Training hardware
- NVIDIA A100
- Chips used
- 256
- Training time
- 480 h
- Training power draw
- 202.3 kW
- Model accessibility
- Open weights (non-commercial)
- 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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