MolPath
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
- Southwest Petroleum University,East China Normal University
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 13 October 2024
- Authors
- Honghao Wang, Acong Zhang, Yuan Zhong, Junlei Tang, Kai Zhang, Ping Li
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology, Materials science
- Task
- Small molecule property 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
ESOL: 1,128 × 0.8 = 902 FreeSolv: 642 × 0.8 = 514 Lipo: 4,200 × 0.8 = 3,360 BBBP: 2,039 × 0.8 = 1,631 Tox21: 7,831 × 0.8 = 6,265 SIDER: 1,427 × 0.8 = 1,142 ClinTox: 1,478 × 0.8 = 1,182 BACE: 1,513 × 0.8 = 1,210 The model is trained on classification for each dataset separately with Tox21 being the largest training dataset.
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
- 5
Sources
Where this record came from and when it was last checked.
- Reference
- Chain-aware graph neural networks for molecular property prediction
- Last updated
- 28 November 2025
What the numbers mean
Background
MolPath was published by Southwest Petroleum University,East China Normal University, in China, in October 2024. The organisation is categorised as academia,Academia.
It works in Biology, Materials science, and is recorded as doing small molecule property prediction.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
MolPath — common questions
Who created MolPath?
MolPath was published by Southwest Petroleum University,East China Normal University, based in China, categorised as academia,Academia.
When was MolPath released?
MolPath 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.
What is MolPath used for?
MolPath works in Biology, Materials science, and is recorded as handling small molecule property prediction. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run MolPath?
None. MolPath 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 MolPath open source?
The licensing for MolPath 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 MolPath have?
No parameter count has been published for MolPath, which is why no memory or speed figure appears on this page.
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.