RiboCode
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Sun Yat-sen University,Rhegen Biotechnology,Chinese Academy of Sciences
- Organisation type
- Academia,Industry,Academia
- Country
- China
- Published
- 8 September 2024
- Authors
- Yupeng Li, Fan Wang, Jiaqi Yang, Zirong Han, Linfeng Chen, Wenbing Jiang, Hao Zhou, Tong Li, Zehua Tang, Jianxiang Deng, Xin He, Gaofeng Zha, Jiekai Hu, Yong Hu, Linping Wu, Changyou Zhan, Caijun Sun, Yao He, Zhi Xie
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- RNA design
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
320 datasets × 10,000 mRNAs/dataset = 3,200,000 data points (3.2 × 10^6 data points)
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Deep Generative Optimization of mRNA Codon Sequences for Enhanced Protein Production and Therapeutic Efficacy
- Last updated
- 28 November 2025
What the numbers mean
About this model
RiboCode was published by Sun Yat-sen University,Rhegen Biotechnology,Chinese Academy of Sciences, in China, in September 2024. The organisation is categorised as academia,Industry,Academia.
It works in Biology, and is recorded as doing rNA design.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
RiboCode — common questions
When was RiboCode released?
RiboCode was published in September 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is RiboCode used for?
RiboCode works in Biology, and is recorded as handling rNA design. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run RiboCode?
None. RiboCode is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is RiboCode open source?
The licensing for RiboCode was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does RiboCode have?
No parameter count has been published for RiboCode, which is why no memory or speed figure appears on this page.
Who created RiboCode?
RiboCode was published by Sun Yat-sen University,Rhegen Biotechnology,Chinese Academy of Sciences, based in China, categorised as academia,Industry,Academia.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.