AI models
Evo 2 40B
Training compute
2.3×10²⁴ FLOP
Parameters
40.3B
Published
Feb 19, 2025
Evo 2 40B is an AI model developed by Arc Institute, Stanford University, NVIDIA, Liquid, University of California (UC) Berkeley, Goodfire and 2 more (United States), first published in February 2025. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm).
Training it took an estimated 2.3×10²⁴ FLOP of compute (estimation method: operation counting,reported). The model has 40,300,000,000 parameters. It was trained on roughly 9.3T datapoints.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Arc Institute, Stanford University, NVIDIA, Liquid, University of California (UC) Berkeley, Goodfire, Columbia University, University of California San Francisco
- Country of organization
- United States
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM)
- Training compute
- 2.3×10²⁴ FLOP
- Compute estimation method
- Operation counting, Reported
- Parameters
- 40,300,000,000
- Dataset size
- 9.3T
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Epoch confidence
- Confident
More from Arc Institute,Stanford University,NVIDIA,Liquid,University of California (UC) Berkeley,Goodfire,Columbia University,University of California San Francisco
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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