GearBind
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
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
- BioGeometry,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de Montréal,Fudan University,HEC Montreal
- Organisation type
- Industry,Academia,Academia,Academia,Academia
- Country
- China, Canada
- Published
- 6 September 2024
- Authors
- Huiyu Cai, Zuobai Zhang, Mingkai Wang, Bozitao Zhong, Quanxiao Li, Yuxuan Zhong, Yanling Wu, Tianlei Ying, Jian Tang
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
"For pretraining, we use a non-redundant subset of CATH v4.3.0 domains, which contains 30,948 experimental protein struc- tures" Binary classification with 1 prediction target per protein
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
- Open — downloadable
- Model access
- Open weights (unrestricted)
- Training code
- Open source
The GearBind inference code, the trained model checkpoints and the dataset preprocessing scripts are available via https://github.com/DeepGraphLearning/GearBind under the Apache 2.0 License.
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
- Citations
- 4
Sources
Where this record came from and when it was last checked.
- Reference
- Pretrainable geometric graph neural network for antibody affinity maturation
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
GearBind was published by BioGeometry,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de Montréal,Fudan University,HEC Montreal, in China, in September 2024. industry,Academia,Academia,Academia,Academia is the category the publisher falls under.
It works in Biology, and is recorded as doing protein design.
Because its weights were released, nothing about running it depends on a provider staying available — it is yours once downloaded.
Answers
GearBind — common questions
What GPU do I need to run GearBind?
We cannot say. GearBind has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
Is GearBind open source?
Its weights are published, so GearBind can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
How many parameters does GearBind have?
No parameter count has been published for GearBind, which is why no memory or speed figure appears on this page.
Who created GearBind?
GearBind was published by BioGeometry,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de Montréal,Fudan University,HEC Montreal, based in China, categorised as industry,Academia,Academia,Academia,Academia.
When was GearBind released?
GearBind 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 GearBind used for?
GearBind works in Biology, and is recorded as handling protein design. These are the areas it was designed around; they describe intent rather than a hard boundary.
Where can I download GearBind?
The weights for GearBind are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
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.