AI models
RNN 1000/5 + RT09 LM (NIST RT05)
Training compute
5×10¹⁶ FLOP
Parameters
77M
Published
Sep 26, 2010
RNN 1000/5 + RT09 LM (NIST RT05) is an AI model developed by Brno University of Technology and Johns Hopkins University (Czechia and United States), first published in September 2010. It works in the speech domain, on tasks such as speech recognition (asr) and transcription. It counts among the frontier models: the systems trained with the most compute of their moment.
Training it took an estimated 5×10¹⁶ FLOP of compute (estimation method: operation counting). The model has 77,039,000 parameters. It was trained on roughly 5.4M datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 6,038 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Brno University of Technology, Johns Hopkins University
- Country of organization
- Czechia, United States
- Domain
- Speech
- Task
- Speech recognition (ASR), Transcription
- Training compute
- 5×10¹⁶ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 77,039,000
- Dataset size
- 5.4M
- Training time
- 1,200 h
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 6,038
- Epoch confidence
- Likely
More from Brno University of Technology,Johns Hopkins University
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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