AI models
RNA-FM
Training compute
2.6×10²¹ FLOP
Published
Aug 8, 2022
RNA-FM is an AI model developed by Chinese University of Hong Kong (CUHK), Fudan University, Shanghai AI Lab, Harbin Institute of Technology, University of Electronic Science and Technology of China, Massachusetts Institute of Technology (MIT) and 3 more (Hong Kong, China and United States), first published in August 2022. It works in the biology domain, on tasks such as rna structure prediction.
Training it took an estimated 2.6×10²¹ FLOP of compute (estimation method: hardware). Training ran on 8 NVIDIA A100 for about 720 hours.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 234 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Chinese University of Hong Kong (CUHK), Fudan University, Shanghai AI Lab, Harbin Institute of Technology, University of Electronic Science and Technology of China, Massachusetts Institute of Technology (MIT), Harvard University, Shanghai Zelixir Biotech, CUHK Shenzhen Research Institute
- Country of organization
- Hong Kong, China, United States
- Domain
- Biology
- Task
- RNA structure prediction
- Training compute
- 2.6×10²¹ FLOP
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA A100
- Chips used
- 8
- Training time
- 720 h
- Training power draw
- 6.4 kW
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 234
- 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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