AI models
JIANG
Training compute
4×10²² FLOP
Published
Aug 1, 2023
JIANG is an AI model developed by K.D. Feddersen (KDF) (China), first published in August 2023. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 4×10²² FLOP of compute (estimation method: hardware). It was trained on roughly 466.7B datapoints. Training ran on 96 NVIDIA A100 SXM4 80 GB for about 1.2K hours.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- K.D. Feddersen (KDF)
- Country of organization
- China
- Domain
- Language
- Task
- Language modeling
- Training compute
- 4×10²² FLOP
- Compute estimation method
- Hardware
- Dataset size
- 466.7B
- Training hardware
- NVIDIA A100 SXM4 80 GB
- Chips used
- 96
- Training time
- 1,200 h
- Training power draw
- 76.3 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 0
- 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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