PPFlow
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
- Zhejiang University (ZJU),Westlake University
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 25 September 2024
- Authors
- Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li
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
Summary of calculations: 15,593 protein-peptide pairs Average residues per pair = 300 (protein) + 12 (peptide) = 312 Total datapoints = 15,593 × 312 = 4.85 × 10^6
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- PPFLOW: Target-aware Peptide Design with Torsional Flow Matching
- Last updated
- 28 November 2025
What the numbers mean
What this model is
PPFlow was published by Zhejiang University (ZJU),Westlake University, in China, in September 2024. It comes out of 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
PPFlow — common questions
When was PPFlow released?
PPFlow 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 PPFlow used for?
PPFlow 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.
What GPU do I need to run PPFlow?
None. PPFlow 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 PPFlow open source?
The licensing for PPFlow 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 PPFlow have?
No parameter count has been published for PPFlow, which is why no memory or speed figure appears on this page.
Who created PPFlow?
PPFlow was published by Zhejiang University (ZJU),Westlake University, 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.