AI models
LSTM-Char-Large
Training compute
2.6×10¹⁵ FLOP
Parameters
19M
Published
Aug 26, 2015
LSTM-Char-Large is an AI model developed by Harvard University and New York University (NYU) (United States), first published in August 2015. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2.6×10¹⁵ FLOP of compute (estimation method: operation counting). The model has 19,000,000 parameters. It was trained on roughly 929K datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 2,033 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Harvard University, New York University (NYU)
- Country of organization
- United States
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2.6×10¹⁵ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 19,000,000
- Dataset size
- 929K
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 2,033
- 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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