AI models
OPT-175B
Training compute
4.3×10²³ FLOP
Parameters
175B
Published
May 2, 2022
OPT-175B is an AI model developed by Meta AI (United States), first published in May 2022. It works in the language domain, on tasks such as language modeling, chat, language modeling/generation and question answering.
Training it took an estimated 4.3×10²³ FLOP of compute (estimation method: reported). The model has 175,000,000,000 parameters. It was trained on roughly 180B datapoints. Training ran on 1,024 NVIDIA A100 SXM4 80 GB for about 794 hours. The compute alone is estimated at $734K in 2023 dollars.
Access: Open weights (non-commercial). Its weights are openly available. The reference paper has 4,716 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Meta AI
- Country of organization
- United States
- Domain
- Language
- Task
- Language modeling, Chat, Language modeling/generation, Question answering
- Training compute
- 4.3×10²³ FLOP
- Compute estimation method
- Reported
- Parameters
- 175,000,000,000
- Dataset size
- 180B
- Training hardware
- NVIDIA A100 SXM4 80 GB
- Chips used
- 1,024
- Training time
- 794 h
- Chip-hours
- 812.5K
- Training power draw
- 822.7 kW
- Training cost (2023 USD)
- $734K
- Numerical format
- FP16
- Model accessibility
- Open weights (non-commercial)
- Open weights
- Yes
- Citations
- 4,716
- Epoch confidence
- Confident
More from Meta AI
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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