AI models
OmniNA
Training compute
2.5×10²¹ FLOP
Parameters
1.7B
Published
Jan 15, 2024
OmniNA is an AI model developed by Tianjin Medical University (China), first published in January 2024. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm).
Training it took an estimated 2.5×10²¹ FLOP of compute (estimation method: operation counting). The model has 1,700,000,000 parameters. Training ran on 8 NVIDIA A100 SXM4 80 GB.
The reference paper has 3 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Tianjin Medical University
- Country of organization
- China
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM)
- Training compute
- 2.5×10²¹ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 1,700,000,000
- Training hardware
- NVIDIA A100 SXM4 80 GB
- Chips used
- 8
- Training power draw
- 6.3 kW
- Citations
- 3
- Epoch confidence
- Likely
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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