ProteinMPNN-DDG
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
- Peptone
- Organisation type
- Industry
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 9 September 2024
- Authors
- Oliver Dutton, Sandro Bottaro, Michele Invernizzi, Istvan Redl, Albert Chung, Falk Hoffmann, Louie Henderson, Stefano Ruschetta, Fabio Airoldi, Benjamin M J Owens, Patrik Foerch, Carlo Fisicaro, Kamil Tamiola
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein inverse folding
- Base model
- ProteinMPNN
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
Total Residues = 5,615,050 = 5.6e6
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- Improving Inverse Folding models at Protein Stability Prediction without additional Training or Data
- Last updated
- 28 November 2025
What the numbers mean
About this model
ProteinMPNN-DDG was published by Peptone, in United Kingdom of Great Britain and Northern Ireland, in September 2024. It comes out of industry.
It works in Biology, and is recorded as doing protein inverse folding.
Its starting point was ProteinMPNN — most models at this scale are adapted from an existing base rather than built from nothing.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
ProteinMPNN-DDG — common questions
How many parameters does ProteinMPNN-DDG have?
No parameter count has been published for ProteinMPNN-DDG, which is why no memory or speed figure appears on this page.
Who created ProteinMPNN-DDG?
ProteinMPNN-DDG was published by Peptone, based in United Kingdom of Great Britain and Northern Ireland, categorised as industry.
When was ProteinMPNN-DDG released?
ProteinMPNN-DDG 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 ProteinMPNN-DDG used for?
ProteinMPNN-DDG works in Biology, and is recorded as handling protein inverse folding. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run ProteinMPNN-DDG?
None. ProteinMPNN-DDG 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 ProteinMPNN-DDG open source?
The licensing for ProteinMPNN-DDG was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
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.