BASIC-L

Training compute

4.1×10²² FLOP

Parameters

3.1B

Published

Nov 19, 2021

BASIC-L is an AI model developed by Google (United States), first published in November 2021. It works in the vision domain, on tasks such as image classification.

Training it took an estimated 4.1×10²² FLOP of compute (estimation method: hardware). The model has 3,070,000,000 parameters. It was trained on roughly 8.9T datapoints. Training ran on Google TPU v4. The compute alone is estimated at $2K in 2023 dollars.

Access: Unreleased. Its weights are not openly released. The reference paper has 241 citations. Epoch AI rates the confidence of this record as likely.

Full record

Organization: Google
Country of organization: United States
Domain: Vision
Task: Image classification
Training compute: 4.1×10²² FLOP
Compute estimation method: Hardware
Parameters: 3,070,000,000
Dataset size: 8.9T
Training hardware: Google TPU v4
Chip-hours: 4.3K
Training cost (2023 USD): $2K
Numerical format: BF16
Model accessibility: Unreleased
Open weights: No
Citations: 241
Epoch confidence: Likely