AI models
SeqVec
Training compute
4.1×10¹⁹ FLOP
Parameters
93M
Published
Dec 17, 2019
SeqVec is an AI model developed by Technical University of Munich (Germany), first published in December 2019. It works in the biology domain, on tasks such as proteins.
Training it took an estimated 4.1×10¹⁹ FLOP of compute (estimation method: hardware). The model has 93,000,000 parameters. Training ran on 5 NVIDIA Titan V for about 508 hours.
Access: Open weights (unrestricted). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Technical University of Munich
- Country of organization
- Germany
- Domain
- Biology
- Task
- Proteins
- Training compute
- 4.1×10¹⁹ FLOP
- Compute estimation method
- Hardware
- Parameters
- 93,000,000
- Training hardware
- NVIDIA Titan V
- Chips used
- 5
- Training time
- 508 h
- Chip-hours
- 2.5K
- Training power draw
- 2.6 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Epoch confidence
- Confident
More from Technical University of Munich
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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