AI models
DITTO
Training compute
3.3×10¹⁸ FLOP
Parameters
750M
Published
Jun 6, 2022
DITTO is an AI model developed by Tsinghua University, Apple, Westlake University and Chinese University of Hong Kong (CUHK) (China, United States and Hong Kong), first published in June 2022. It works in the language domain, on tasks such as language modeling/generation and text summarization.
Training it took an estimated 3.3×10¹⁸ FLOP of compute (estimation method: operation counting). The model has 750,000,000 parameters. It was trained on roughly 103M datapoints. Training ran on 8 NVIDIA V100.
Access: Unreleased. Its weights are not openly released. The reference paper has 109 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Tsinghua University, Apple, Westlake University, Chinese University of Hong Kong (CUHK)
- Country of organization
- China, United States, Hong Kong
- Domain
- Language
- Task
- Language modeling/generation, Text summarization
- Training compute
- 3.3×10¹⁸ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 750,000,000
- Dataset size
- 103M
- Training hardware
- NVIDIA V100
- Chips used
- 8
- Training power draw
- 4.8 kW
- Numerical format
- FP16
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 109
- 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.
← All ai models