AI models
ReLU-Speech
Training compute
1.3×10¹⁷ FLOP
Parameters
101.7M
Published
May 26, 2013
ReLU-Speech is an AI model developed by Google, University of Toronto and New York University (NYU) (United States and Canada), first published in May 2013. It works in the speech domain, on tasks such as speech recognition (asr).
Training it took an estimated 1.3×10¹⁷ FLOP of compute (estimation method: hardware). The model has 101,706,240 parameters.
Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Google, University of Toronto, New York University (NYU)
- Country of organization
- United States, Canada
- Domain
- Speech
- Task
- Speech recognition (ASR)
- Training compute
- 1.3×10¹⁷ FLOP
- Compute estimation method
- Hardware
- Parameters
- 101,706,240
- Training time
- 168 h
- 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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