gLM

Training compute

2.3×10²⁰ FLOP

Parameters

1B

Published

Apr 8, 2023

gLM is an AI model developed by Harvard University (United States), first published in April 2023. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm).

Training it took an estimated 2.3×10²⁰ FLOP of compute (estimation method: hardware). The model has 1,000,000,000 parameters. Training ran on NVIDIA A100.

Access: Open weights (non-commercial). Its weights are openly available. It is built on top of ESM2-650M. Epoch AI rates the confidence of this record as likely.

Full record

Organization: Harvard University
Country of organization: United States
Domain: Biology
Task: Protein or nucleotide language model (pLM/nLM)
Training compute: 2.3×10²⁰ FLOP
Compute estimation method: Hardware
Parameters: 1,000,000,000
Training hardware: NVIDIA A100
Model accessibility: Open weights (non-commercial)
Open weights: Yes
Base model: ESM2-650M
Epoch confidence: Likely