AI models
ELMo
Training compute
3.3×10¹⁵ FLOP
Parameters
94M
Published
Feb 1, 2018
ELMo is an AI model developed by University of Washington and Allen Institute for AI (United States), first published in February 2018. It works in the language domain, on tasks such as question answering, sentiment classification and language modeling.
Training it took an estimated 3.3×10¹⁵ FLOP of compute (estimation method: third-party estimation). The model has 94,000,000 parameters. It was trained on roughly 2B datapoints.
The reference paper has 12,156 citations. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- University of Washington, Allen Institute for AI
- Country of organization
- United States
- Domain
- Language
- Task
- Question answering, Sentiment classification, Language modeling
- Training compute
- 3.3×10¹⁵ FLOP
- Compute estimation method
- Third-party estimation
- Parameters
- 94,000,000
- Dataset size
- 2B
- Citations
- 12,156
- Epoch confidence
- Speculative
More from University of Washington,Allen Institute for AI
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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