AI models
OmegaPLM
Training compute
10²² FLOP
Parameters
670M
Published
Jul 22, 2022
OmegaPLM is an AI model developed by Massachusetts Institute of Technology (MIT) and Westlake University (United States and China), first published in July 2022. It works in the biology domain, on tasks such as proteins and protein folding prediction.
Training it took an estimated 10²² FLOP of compute (estimation method: hardware). The model has 670,000,000 parameters. It was trained on roughly 1.3T datapoints. Training ran on NVIDIA A100 SXM4 80 GB. The compute alone is estimated at $52K in 2023 dollars.
Access: Unreleased. Its weights are not openly released. The reference paper has 445 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Massachusetts Institute of Technology (MIT), Westlake University
- Country of organization
- United States, China
- Domain
- Biology
- Task
- Proteins, Protein folding prediction
- Training compute
- 10²² FLOP
- Compute estimation method
- Hardware
- Parameters
- 670,000,000
- Dataset size
- 1.3T
- Training hardware
- NVIDIA A100 SXM4 80 GB
- Chip-hours
- 61.4K
- Training cost (2023 USD)
- $52K
- Numerical format
- TF32
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 445
- 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.
← All ai models