Qwen2.5-32B

Training compute

3.5×10²⁴ FLOP

Parameters

32.5B

Published

Sep 17, 2024

Qwen2.5-32B is an AI model developed by Alibaba (China), first published in September 2024. It works in the language domain, on tasks such as language modeling/generation, question answering and quantitative reasoning.

Training it took an estimated 3.5×10²⁴ FLOP of compute (estimation method: operation counting). The model has 32,500,000,000 parameters. It was trained on roughly 18T datapoints.

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

Full record

Organization: Alibaba
Country of organization: China
Domain: Language
Task: Language modeling/generation, Question answering, Quantitative reasoning
Training compute: 3.5×10²⁴ FLOP
Compute estimation method: Operation counting
Parameters: 32,500,000,000
Dataset size: 18T
Numerical format: BF16
Model accessibility: Open weights (unrestricted)
Open weights: Yes
Epoch confidence: Confident