AI models
GenSLM
Training compute
1.4×10²¹ FLOP
Parameters
25B
Published
Oct 11, 2022
GenSLM is an AI model developed by University of Chicago, NVIDIA, Harvard University, Cerebras Systems, Technical University of Munich and California Institute of Technology (United States and Germany), first published in October 2022. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm).
Training it took an estimated 1.4×10²¹ FLOP of compute (estimation method: reported). The model has 25,000,000,000 parameters. It was trained on roughly 225.3B datapoints.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 114 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- University of Chicago, NVIDIA, Harvard University, Cerebras Systems, Technical University of Munich, California Institute of Technology
- Country of organization
- United States, Germany
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM)
- Training compute
- 1.4×10²¹ FLOP
- Compute estimation method
- Reported
- Parameters
- 25,000,000,000
- Dataset size
- 225.3B
- Numerical format
- FP16
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 114
- 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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