4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment
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
- Fudan University,Shanghai Academy of Artificial Intelligence for Science,Nanjing University
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 12 September 2024
- Authors
- Kaihui Cheng, Ce Liu, Qingkun Su, Jun Wang, Liwei Zhang, Yining Tang, Yao Yao, Siyu Zhu, Yuan Qi
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein folding 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.
- Training data
- tokens
- Epochs
- 550
This model is not trained on a token level and processes a protein in a single forward pass. 764 proteins * 32 steps = 24448
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- How it was established
- Hardware
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
- 1
- Power draw
- 433 W
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
the page is not accessible anymore https://github.com/fudan-generative-vision/AlphaFolding
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
- 4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment
- Last updated
- 28 November 2025
What the numbers mean
What this model is
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment was published by Fudan University,Shanghai Academy of Artificial Intelligence for Science,Nanjing University, in the country recorded as China, during September 2024. It comes out of an organisation categorised as academia,Academia.
It works in the domain of Biology, and is recorded as performing the task of protein folding prediction.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment — common questions
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— 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.
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— who created it?
It was published by Fudan University,Shanghai Academy of Artificial Intelligence for Science,Nanjing University, based in China, an organisation categorised as academia,Academia.
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— when was it released?
It 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.
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of protein folding prediction. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— 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.
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
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.