AI models
genCNN + dyn eval
Training compute
3.4×10¹⁶ FLOP
Parameters
8M
Published
Mar 17, 2015
genCNN + dyn eval is an AI model developed by Chinese Academy of Sciences, Huawei Noah's Ark Lab and Dublin City University (China and Ireland), first published in March 2015. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 3.4×10¹⁶ FLOP of compute (estimation method: hardware,operation counting). The model has 8,000,000 parameters. It was trained on roughly 929K datapoints. Training ran on NVIDIA Tesla K40s for about 48 hours.
Access: Unreleased. Its weights are not openly released. The reference paper has 33 citations. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- Chinese Academy of Sciences, Huawei Noah's Ark Lab, Dublin City University
- Country of organization
- China, Ireland
- Domain
- Language
- Task
- Language modeling
- Training compute
- 3.4×10¹⁶ FLOP
- Compute estimation method
- Hardware, Operation counting
- Parameters
- 8,000,000
- Dataset size
- 929K
- Training hardware
- NVIDIA Tesla K40s
- Training time
- 48 h
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 33
- Epoch confidence
- Speculative
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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