OPT-6.7B

Training compute

1.2×10²² FLOP

Parameters

6.7B

Published

Jun 21, 2022

OPT-6.7B is an AI model developed by Meta AI (United States), first published in June 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 1.2×10²² FLOP of compute (estimation method: comparison with other models). The model has 6,700,000,000 parameters. It was trained on roughly 180B datapoints.

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: 1.2×10²² FLOP
Compute estimation method: Comparison with other models
Parameters: 6,700,000,000
Dataset size: 180B
Model accessibility: Open weights (non-commercial)
Open weights: Yes
Citations: 4,716
Epoch confidence: Confident