AI models
RGC+ASQ (PTB)
Training compute
1.2×10¹⁶ FLOP
Parameters
53.5M
Published
Aug 13, 2018
RGC+ASQ (PTB) is an AI model developed by Tsinghua University and University of California Los Angeles (UCLA) (China and United States), first published in August 2018. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 1.2×10¹⁶ FLOP of compute. The model has 53,477,376 parameters. Training ran on 8 NVIDIA Titan V.
Access: Unreleased. Its weights are not openly released. The reference paper has 29 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Tsinghua University, University of California Los Angeles (UCLA)
- Country of organization
- China, United States
- Domain
- Language
- Task
- Language modeling
- Training compute
- 1.2×10¹⁶ FLOP
- Parameters
- 53,477,376
- Training hardware
- NVIDIA Titan V
- Chips used
- 8
- Training power draw
- 4.1 kW
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 29
- Epoch confidence
- Likely
More from Tsinghua University,University of California Los Angeles (UCLA)
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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