AlphaFold

Training compute

10²⁰ FLOP

Parameters

16.3M

Published

Jan 15, 2020

AlphaFold is an AI model developed by DeepMind (United Kingdom), first published in January 2020. It works in the biology domain, on tasks such as protein folding prediction and proteins.

Training it took an estimated 10²⁰ FLOP of compute (estimation method: hardware,third-party estimation). The model has 16,340,840 parameters. It was trained on roughly 6.6B datapoints.

Access: Unreleased. Its weights are not openly released. The reference paper has 2,773 citations. Epoch AI rates the confidence of this record as speculative.

Full record

Organization: DeepMind
Country of organization: United Kingdom
Domain: Biology
Task: Protein folding prediction, Proteins
Training compute: 10²⁰ FLOP
Compute estimation method: Hardware, Third-party estimation
Parameters: 16,340,840
Dataset size: 6.6B
Training time: 120 h
Model accessibility: Unreleased
Open weights: No
Citations: 2,773
Epoch confidence: Speculative