OPT-30B

Training compute

5.4×10²² FLOP

Parameters

30B

Published

Jun 21, 2022

OPT-30B 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 5.4×10²² FLOP of compute (estimation method: operation counting). The model has 30,000,000,000 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: 5.4×10²² FLOP
Compute estimation method: Operation counting
Parameters: 30,000,000,000
Dataset size: 180B
Model accessibility: Open weights (non-commercial)
Open weights: Yes
Citations: 4,716
Epoch confidence: Confident