OPUS-Design
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 AI Lab,Harcam Biomedicines
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 29 August 2024
- Authors
- Gang Xu, Yulu Yang, Yiqiu Zhang, Qinghua Wang, Jianpeng Ma
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
- tokens
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 V100
- Chips used
- 4
- Power draw
- 2.4 kW
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 code and pre-trained models of OPUS-Design as well as the test sets used in the study can be downloaded from http://github.com/OPUS-MaLab/opus_design. They are freely available for academic usage. [unaccessible now]
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
- OPUS-Design: Designing Protein Sequence from Backbone Structure with 3DCNN and Protein Language Model
- Last updated
- 28 November 2025
What the numbers mean
About this model
OPUS-Design was published by Fudan University,Shanghai AI Lab,Harcam Biomedicines, in China, in August 2024. The organisation is categorised as academia,Academia.
It works in Biology, and is recorded as doing protein design.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
OPUS-Design — common questions
When was OPUS-Design released?
OPUS-Design was published in August 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 OPUS-Design used for?
OPUS-Design 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.
What GPU do I need to run OPUS-Design?
None. OPUS-Design 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 OPUS-Design open source?
No. OPUS-Design has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does OPUS-Design have?
No parameter count has been published for OPUS-Design, which is why no memory or speed figure appears on this page.
Who created OPUS-Design?
OPUS-Design was published by Fudan University,Shanghai AI Lab,Harcam Biomedicines, based in China, categorised as academia,Academia.
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.