AI models
MolPhenix
Training compute
4.3×10¹⁸ FLOP
Parameters
38.7M
Published
Sep 10, 2024
MolPhenix is an AI model developed by Valence Labs, University of British Columbia (UBC), Vector Institute, University of Toronto, University of Montreal / Université de Montréal and Mila - Quebec AI (originally Montreal Institute for Learning Algorithms) (Canada), first published in September 2024. It works in the biology domain, on tasks such as cell biology.
Training it took an estimated 4.3×10¹⁸ FLOP of compute (estimation method: hardware). The model has 38,700,000 parameters. Training ran on 1 NVIDIA A100 for about 9.5 hours.
Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Valence Labs, University of British Columbia (UBC), Vector Institute, University of Toronto, University of Montreal / Université de Montréal, Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
- Country of organization
- Canada
- Domain
- Biology
- Task
- Cell Biology
- Training compute
- 4.3×10¹⁸ FLOP
- Compute estimation method
- Hardware
- Parameters
- 38,700,000
- Training hardware
- NVIDIA A100
- Chips used
- 1
- Training time
- 10 h
- Training power draw
- 433 W
- 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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