AI models
ERNIE-ViLG 2.0
Training compute
4.7×10²² FLOP
Parameters
24B
Published
Mar 28, 2023
ERNIE-ViLG 2.0 is an AI model developed by Baidu and Wuhan University of Science and Technology (China), first published in March 2023. It works in the image generation domain, on tasks such as image generation.
Training it took an estimated 4.7×10²² FLOP of compute (estimation method: hardware). The model has 24,000,000,000 parameters. It was trained on roughly 11.1T datapoints. Training ran on 320 NVIDIA A100 for about 432 hours.
Access: API access. Its weights are not openly released. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Baidu, Wuhan University of Science and Technology
- Country of organization
- China
- Domain
- Image generation
- Task
- Image generation
- Training compute
- 4.7×10²² FLOP
- Compute estimation method
- Hardware
- Parameters
- 24,000,000,000
- Dataset size
- 11.1T
- Training hardware
- NVIDIA A100
- Chips used
- 320
- Training time
- 432 h
- Training power draw
- 255.2 kW
- Model accessibility
- API access
- Open weights
- No
- Epoch confidence
- Confident
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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