AI models
MMLSTM (WT-2)
Training compute
1.9×10¹⁷ FLOP
Parameters
32.3M
Published
Dec 5, 2019
MMLSTM (WT-2) is an AI model developed by Beijing University of Posts and Telecommunications and University of West London (China and United Kingdom), first published in December 2019. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 1.9×10¹⁷ FLOP of compute (estimation method: operation counting). The model has 32,300,000 parameters. It was trained on roughly 2M datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 19 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Beijing University of Posts and Telecommunications, University of West London
- Country of organization
- China, United Kingdom
- Domain
- Language
- Task
- Language modeling
- Training compute
- 1.9×10¹⁷ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 32,300,000
- Dataset size
- 2M
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 19
- Epoch confidence
- Likely
More from Beijing University of Posts and Telecommunications,University of West London
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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