AI models
ProtBERT-UniRef
Training compute
7.3×10²¹ FLOP
Parameters
420M
Published
May 4, 2021
ProtBERT-UniRef is an AI model developed by Technical University of Munich, NVIDIA, Seoul National University, Google, Oak Ridge National Laboratory and Med AI Technology (Germany, United States, South Korea and China), first published in May 2021. It works in the biology domain, on tasks such as proteins and protein or nucleotide language model (plm/nlm).
Training it took an estimated 7.3×10²¹ FLOP of compute. The model has 420,000,000 parameters. Training ran on 512 Google TPU v3.
The reference paper has 5 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Technical University of Munich, NVIDIA, Seoul National University, Google, Oak Ridge National Laboratory, Med AI Technology
- Country of organization
- Germany, United States, South Korea, China
- Domain
- Biology
- Task
- Proteins, Protein or nucleotide language model (pLM/nLM)
- Training compute
- 7.3×10²¹ FLOP
- Parameters
- 420,000,000
- Training hardware
- Google TPU v3
- Chips used
- 512
- Training power draw
- 466.5 kW
- Citations
- 5
- Epoch confidence
- Confident
More from Technical University of Munich,NVIDIA,Seoul National University,Google,Oak Ridge National Laboratory,Med AI Technology
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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