AI models
ProGen2-base
Training compute
1.1×10²¹ FLOP
Parameters
764M
Published
Jun 27, 2022
ProGen2-base is an AI model developed by Salesforce Research, Columbia University and Johns Hopkins University (United States), first published in June 2022. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm).
Training it took an estimated 1.1×10²¹ FLOP of compute (estimation method: operation counting,third-party estimation). The model has 764,000,000 parameters. Training ran on Google TPU v3.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 507 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Salesforce Research, Columbia University, Johns Hopkins University
- Country of organization
- United States
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM)
- Training compute
- 1.1×10²¹ FLOP
- Compute estimation method
- Operation counting, Third-party estimation
- Parameters
- 764,000,000
- Training hardware
- Google TPU v3
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 507
- Epoch confidence
- Confident
More from Salesforce Research,Columbia University,Johns Hopkins University
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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