IEV2MOL
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
- Tokyo Institute of Technology
- Organisation type
- Academia
- Country
- Japan
- Published
- 10 October 2024
- Authors
- Mami Ozawa, Shogo Nakamura, Nobuaki Yasuo, Masakazu Sekijima
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Drug discovery
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
- 73,585,425 tokens
Main dataset: 981,139 compounds represented by SMILES strings. Estimating ~40 characters per compound Total prediction targets: 981139 * 40 = 39245560
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- How it was established
- Hardware
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
- IEV2Mol: Molecular Generative Model Considering Protein-Ligand Interaction Energy Vectors
- Last updated
- 28 November 2025
What the numbers mean
What this model is
IEV2MOL was published by Tokyo Institute of Technology, in Japan, in October 2024. The organisation is categorised as academia.
It works in Biology, and is recorded as doing drug discovery.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
It was trained on about 73,585,425 tokens of text.
Answers
IEV2MOL — common questions
How many parameters does IEV2MOL have?
No parameter count has been published for IEV2MOL, which is why no memory or speed figure appears on this page.
Who created IEV2MOL?
IEV2MOL was published by Tokyo Institute of Technology, based in Japan, categorised as academia.
When was IEV2MOL released?
IEV2MOL 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 IEV2MOL used for?
IEV2MOL works in Biology, and is recorded as handling drug discovery. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run IEV2MOL?
None. IEV2MOL 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 IEV2MOL open source?
The licensing for IEV2MOL was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
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.