OLMo 2 32B

Training compute

1.3×10²⁴ FLOP

Parameters

32B

Published

Mar 13, 2025

OLMo 2 32B is an AI model developed by Allen Institute for AI (United States), first published in March 2025. It works in the language domain, on tasks such as language modeling/generation and question answering.

Training it took an estimated 1.3×10²⁴ FLOP of compute (estimation method: reported). The model has 32,000,000,000 parameters. It was trained on roughly 4T datapoints. Training ran on NVIDIA H100 SXM5 80GB.

Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Allen Institute for AI
Country of organization: United States
Domain: Language
Task: Language modeling/generation, Question answering
Training compute: 1.3×10²⁴ FLOP
Compute estimation method: Reported
Parameters: 32,000,000,000
Dataset size: 4T
Training hardware: NVIDIA H100 SXM5 80GB
Model accessibility: Open weights (unrestricted)
Open weights: Yes
Epoch confidence: Confident