AI models
MemSizer (language modeling)
Training compute
7.3×10¹⁸ FLOP
Parameters
357M
Published
Mar 23, 2022
MemSizer (language modeling) is an AI model developed by Meta AI and Chinese University of Hong Kong (CUHK) (United States and Hong Kong), first published in March 2022. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 7.3×10¹⁸ FLOP of compute (estimation method: operation counting). The model has 357,000,000 parameters. It was trained on roughly 103M datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 6 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Meta AI, Chinese University of Hong Kong (CUHK)
- Country of organization
- United States, Hong Kong
- Domain
- Language
- Task
- Language modeling
- Training compute
- 7.3×10¹⁸ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 357,000,000
- Dataset size
- 103M
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 6
- Epoch confidence
- Likely
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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