Loop-Diffusion
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 Washington
- Organisation type
- Academia
- Country
- United States of America
- Published
- 26 September 2024
- Authors
- Kevin Borisiak, Gian Marco Visani, Armita Nourmohammad
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein 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
- 77,940,000 tokens
433,000 total datapoints = 433k atomic neighborhoods from 20,000 protein structures Final result: 4.33e5 datapoints
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
- Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Loop-Diffusion was published by University of Washington, in United States of America, in September 2024. The organisation is categorised as academia.
It works in Biology, and is recorded as doing protein design.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
It was trained on about 77,940,000 tokens of text.
Answers
Loop-Diffusion — common questions
What GPU do I need to run Loop-Diffusion?
None. Loop-Diffusion 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 Loop-Diffusion open source?
The licensing for Loop-Diffusion 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 Loop-Diffusion have?
No parameter count has been published for Loop-Diffusion, which is why no memory or speed figure appears on this page.
Who created Loop-Diffusion?
Loop-Diffusion was published by University of Washington, based in United States of America, categorised as academia.
When was Loop-Diffusion released?
Loop-Diffusion 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 Loop-Diffusion used for?
Loop-Diffusion works in Biology, and is recorded as handling protein design. 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.