AI models
NLM
Training compute
2.8×10¹⁹ FLOP
Parameters
247M
Published
Sep 9, 2021
NLM is an AI model developed by Carnegie Mellon University (CMU) and University of California San Diego (United States), first published in September 2021. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2.8×10¹⁹ FLOP of compute (estimation method: operation counting). The model has 247,000,512 parameters. Training ran on 1 NVIDIA GeForce RTX 3090.
Access: Unreleased. Its weights are not openly released. The reference paper has 123 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Carnegie Mellon University (CMU), University of California San Diego
- Country of organization
- United States
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2.8×10¹⁹ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 247,000,512
- Training hardware
- NVIDIA GeForce RTX 3090
- Chips used
- 1
- Training power draw
- 388 W
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 123
- 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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