EnzymeFlow
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
- McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Hong Kong University of Science and Technology (HKUST),University of Washington,Microsoft Research,DeepMind,Shanghai Jiao Tong University,University of Montreal / Université de Montréal
- Organisation type
- Academia,Academia,Academia,Academia,Industry,Industry,Academia,Academia
- Country
- Canada, Hong Kong, United States of America, United Kingdom of Great Britain and Northern Ireland, China
- Published
- 1 October 2024
- Authors
- Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K. Yang, Guy Wolf, Doina Precup, Shuangjia Zheng
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
53,483 enzyme-reaction pairs were used to train EnzymeFlow after homology filtering Initial dataset: 328,192 Raw dataset before filtering: 232,520 Final filtered dataset: 53,483
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 (non-commercial)
- Training code
- Open (non-commercial)
Creative Commons Attribution-NonCommercial 4.0 International Public License https://github.com/WillHua127/EnzymeFlow?tab=readme-ov-file
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
- EnzymeFlow: Reaction-conditioned Enzyme Catalytic Pocket Design
- Last updated
- 28 November 2025
What the numbers mean
Background
EnzymeFlow was published by McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Hong Kong University of Science and Technology (HKUST),University of Washington,Microsoft Research,DeepMind,Shanghai Jiao Tong University,University of Montreal / Université de Montréal, in Canada, in October 2024. The organisation is categorised as academia,Academia,Academia,Academia,Industry,Industry,Academia,Academia.
It works in Biology, and is recorded as doing protein design.
The weights being open is what puts this page in the calculator rather than only in the catalogue: it is a model you can actually hold.
Answers
EnzymeFlow — common questions
What is EnzymeFlow used for?
EnzymeFlow 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.
Where can I download EnzymeFlow?
The weights for EnzymeFlow are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
What GPU do I need to run EnzymeFlow?
We cannot say. EnzymeFlow 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 EnzymeFlow open source?
Its weights are published, so EnzymeFlow 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 EnzymeFlow have?
No parameter count has been published for EnzymeFlow, which is why no memory or speed figure appears on this page.
Who created EnzymeFlow?
EnzymeFlow was published by McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Hong Kong University of Science and Technology (HKUST),University of Washington,Microsoft Research,DeepMind,Shanghai Jiao Tong University,University of Montreal / Université de Montréal, based in Canada, categorised as academia,Academia,Academia,Academia,Industry,Industry,Academia,Academia.
When was EnzymeFlow released?
EnzymeFlow was published in October 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.
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.