AI models
Rita-XLarge
Training compute
8.6×10²⁰ FLOP
Parameters
1.2B
Published
Jul 14, 2022
Rita-XLarge is an AI model developed by LightOn, Harvard University and University of Oxford (France, United States and United Kingdom), first published in July 2022. It works in the biology domain, on tasks such as proteins and protein or nucleotide language model (plm/nlm).
Training it took an estimated 8.6×10²⁰ FLOP of compute (estimation method: reported). The model has 1,200,000,000 parameters. It was trained on roughly 150B datapoints. Training ran on NVIDIA V100.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 128 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- LightOn, Harvard University, University of Oxford
- Country of organization
- France, United States, United Kingdom
- Domain
- Biology
- Task
- Proteins, Protein or nucleotide language model (pLM/nLM)
- Training compute
- 8.6×10²⁰ FLOP
- Compute estimation method
- Reported
- Parameters
- 1,200,000,000
- Dataset size
- 150B
- Training hardware
- NVIDIA V100
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 128
- 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.
← All ai models