VGG19

Training compute

1.1×10¹⁹ FLOP

Parameters

144M

Published

Sep 4, 2014

VGG19 is an AI model developed by University of Oxford (United Kingdom), first published in September 2014. It works in the vision domain, on tasks such as image classification. It counts among the frontier models: the systems trained with the most compute of their moment.

Training it took an estimated 1.1×10¹⁹ FLOP of compute (estimation method: third-party estimation). The model has 144,000,000 parameters. It was trained on roughly 1.3M datapoints.

The reference paper has 111,439 citations. Epoch AI rates the confidence of this record as likely.

Full record

Organization: University of Oxford
Country of organization: United Kingdom
Domain: Vision
Task: Image classification
Training compute: 1.1×10¹⁹ FLOP
Compute estimation method: Third-party estimation
Parameters: 144,000,000
Dataset size: 1.3M
Numerical format: FP32
Citations: 111,439
Epoch confidence: Likely