AI models
Transformer local-attention (NesT-B)
Training compute
2.4×10¹⁹ FLOP
Parameters
90.1M
Published
May 26, 2021
Transformer local-attention (NesT-B) is an AI model developed by Google Cloud and Google Research (United States), first published in May 2021. It works in the vision domain, on tasks such as image classification and image generation.
Training it took an estimated 2.4×10¹⁹ FLOP of compute (estimation method: operation counting). The model has 90,100,000 parameters. It was trained on roughly 1.3M datapoints.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 5,734 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Google Cloud, Google Research
- Country of organization
- United States
- Domain
- Vision
- Task
- Image classification, Image generation
- Training compute
- 2.4×10¹⁹ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 90,100,000
- Dataset size
- 1.3M
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 5,734
- 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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