AF2RAVE
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 Maryland
- Organisation type
- Academia
- Country
- United States of America
- Published
- 10 April 2024
- Authors
- Xinyu Gu, Akashnathan Aranganathan, Pratyush Tiwary
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Drug discovery
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
Does not train a new model. Previous calculations below Initial simulations: 12 × (48.5×10^-9 / 2×10^-15) = 291×10^6 steps Umbrella sampling: 12 × (11×11) × (90×10^-9 / 2×10^-15) = 6.534×10^10 steps Total: 291×10^6 + 6.534×10^10 = 6.563×10^10 steps Conservative estimate: 1.6×10^10 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
- Unknown
- Citations
- 18
Sources
Where this record came from and when it was last checked.
- Reference
- Empowering AlphaFold2 for Protein Conformation-Selective Drug Discovery with AlphaFold2-RAVE
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
AF2RAVE was published by University of Maryland, in the country recorded as United States of America, during April 2024. The publishing organisation is categorised as academia.
It works in the domain of Biology, and is recorded as performing the task of drug discovery.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
AF2RAVE — common questions
AF2RAVE— 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.
AF2RAVE— 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.
AF2RAVE— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
AF2RAVE— who created it?
It was published by University of Maryland, based in United States of America, an organisation categorised as academia.
AF2RAVE— when was it released?
It was published in April 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.
AF2RAVE— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of drug discovery. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.