AI models
ESM2-35M
Training compute
2.1×10²⁰ FLOP
Parameters
35M
Published
Jul 21, 2022
ESM2-35M is an AI model developed by Meta AI, New York University (NYU), Stanford University and Massachusetts Institute of Technology (MIT) (United States), first published in July 2022. It works in the biology domain, on tasks such as proteins, protein or nucleotide language model (plm/nlm) and protein folding prediction.
Training it took an estimated 2.1×10²⁰ FLOP of compute. The model has 35,000,000 parameters. It was trained on roughly 15.4B datapoints.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 636 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Meta AI, New York University (NYU), Stanford University, Massachusetts Institute of Technology (MIT)
- Country of organization
- United States
- Domain
- Biology
- Task
- Proteins, Protein or nucleotide language model (pLM/nLM), Protein folding prediction
- Training compute
- 2.1×10²⁰ FLOP
- Parameters
- 35,000,000
- Dataset size
- 15.4B
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 636
- Epoch confidence
- Confident
More from Meta AI,New York University (NYU),Stanford University,Massachusetts Institute of Technology (MIT)
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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