AI models
DeepLoc
Training compute
5.8×10¹⁷ FLOP
Published
Jul 7, 2017
DeepLoc is an AI model developed by Technical University of Denmark and University of Copenhagen (Denmark), first published in July 2017. It works in the biology domain, on tasks such as protein localization prediction.
Training it took an estimated 5.8×10¹⁷ FLOP of compute (estimation method: hardware). Training ran on 1 NVIDIA GeForce GTX TITAN X for about 80 hours.
Access: Hosted access (no API). Its weights are not openly released. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Technical University of Denmark, University of Copenhagen
- Country of organization
- Denmark
- Domain
- Biology
- Task
- Protein localization prediction
- Training compute
- 5.8×10¹⁷ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA GeForce GTX TITAN X
- Chips used
- 1
- Training time
- 80 h
- Training power draw
- 287 W
- Model accessibility
- Hosted access (no API)
- Open weights
- No
- Epoch confidence
- Likely
More from Technical University of Denmark,University of Copenhagen
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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