AlphaGenome

Training compute

1.4×10²² FLOP

Parameters

450M

Published

Jun 25, 2025

AlphaGenome is an AI model developed by Google DeepMind (United States), first published in June 2025. It works in the biology domain, on tasks such as gene expression enhancement, gene expression profile generation, molecular property prediction and 4 more.

Training it took an estimated 1.4×10²² FLOP of compute (estimation method: hardware). The model has 450,000,000 parameters. Training ran on Google TPU v3,NVIDIA H100 SXM5 80GB.

Access: API access. Its weights are not openly released. Epoch AI rates the confidence of this record as likely.

Full record

Organization: Google DeepMind
Country of organization: United States
Domain: Biology
Task: Gene expression enhancement, Gene expression profile generation, Molecular property prediction, Mutation prediction, Protein-DNA binding prediction, Transcriptomic prediction, RNA structure prediction
Training compute: 1.4×10²² FLOP
Compute estimation method: Hardware
Parameters: 450,000,000
Training hardware: Google TPU v3, NVIDIA H100 SXM5 80GB
Model accessibility: API access
Open weights: No
Epoch confidence: Likely