AI models
WeLM
Training compute
2.5×10²² FLOP
Parameters
10B
Published
May 16, 2023
WeLM is an AI model developed by WeChat AI (China), first published in May 2023. It works in the language domain, on tasks such as language modeling/generation and translation.
Training it took an estimated 2.5×10²² FLOP of compute (estimation method: hardware). The model has 10,000,000,000 parameters. It was trained on roughly 262B datapoints. Training ran on 128 NVIDIA A100 SXM4 40 GB for about 576 hours.
The reference paper has 25 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- WeChat AI
- Country of organization
- China
- Domain
- Language
- Task
- Language modeling/generation, Translation
- Training compute
- 2.5×10²² FLOP
- Compute estimation method
- Hardware
- Parameters
- 10,000,000,000
- Dataset size
- 262B
- Training hardware
- NVIDIA A100 SXM4 40 GB
- Chips used
- 128
- Training time
- 576 h
- Chip-hours
- 73.7K
- Training power draw
- 102.0 kW
- Citations
- 25
- 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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