AI models
AlexNet + coordinating filters
Training compute
4.7×10¹⁷ FLOP
Parameters
60M
Published
Mar 28, 2017
AlexNet + coordinating filters is an AI model developed by University of Pittsburgh and Duke University (United States), first published in March 2017. It works in the vision domain, on tasks such as image classification.
Training it took an estimated 4.7×10¹⁷ FLOP of compute (estimation method: comparison with other models). The model has 60,000,000 parameters.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 172 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- University of Pittsburgh, Duke University
- Country of organization
- United States
- Domain
- Vision
- Task
- Image classification
- Training compute
- 4.7×10¹⁷ FLOP
- Compute estimation method
- Comparison with other models
- Parameters
- 60,000,000
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 172
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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