RNAformer
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
- University of Freiburg
- Organisation type
- Academia
- Country
- Germany
- Published
- 1 December 2024
- Authors
- Jörg K.H. Franke, Frederic Runge, Ryan Köksal, Rolf Backofen, Frank Hutter
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- RNA structure prediction
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.
- Parameters
- 32M
- Training data
- tokens
- Biophysical Model: 410,408 (table b1)
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA A100
- Chips used
- 4
- Power draw
- 3.1 kW
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 14
Sources
Where this record came from and when it was last checked.
- Reference
- RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction
- Last updated
- 1 December 2025
What the numbers mean
What this model is
RNAformer was published by University of Freiburg, in the country recorded as Germany, during December 2024. The category the publisher falls under is academia.
It works in the domain of Biology, and is recorded as performing the task of rNA structure prediction.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
RNAformer — common questions
RNAformer— what GPU do I need to run it?
None. This 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.
RNAformer— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
RNAformer— how many parameters does it have?
It has a parameter count of 32M. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
RNAformer— who created it?
It was published by University of Freiburg, based in Germany, an organisation categorised as academia.
RNAformer— when was it released?
It was published in December 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.
RNAformer— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of rNA structure prediction. 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.
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.