Precious3GPT
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
- Insilico Medicine AI,Harvard Medical School
- Organisation type
- Industry,Academia
- Country
- Hong Kong, United States of America
- Published
- 5 July 2024
- Authors
- Fedor Galkin, Vladimir Naumov, Stefan Pushkov, Denis Sidorenko, Anatoly Urban, Diana Zagirova, Khadija M. Alawi, Alex Aliper, Ruslan Gumerov, Aleksandr Kalashnikov, Sabina Mukba, Aleksandra Pogorelskaya, Feng Ren, Anastasia Shneyderman, Qiuqiong Tang, Deyong Xiao, Alexander Tyshkovskiy, Kejun Ying, Vadim N. Gladyshev, Alex Zhavoronkov
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.
- Parameters
- 89M
- Training data
- tokens
- Epochs
- 15
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA RTX A6000
- Chips used
- 5
- Power draw
- 3.0 kW
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 1
Sources
Where this record came from and when it was last checked.
- Reference
- Precious3GPT: Multimodal Multi-Species Multi-Omics Multi-Tissue Transformer for Aging Research and Drug Discovery
- Last updated
- 28 November 2025
What the numbers mean
About this model
Precious3GPT was published by Insilico Medicine AI,Harvard Medical School, in the country recorded as Hong Kong, during July 2024. It comes out of an organisation categorised as industry,Academia.
It works in the domain of Biology, and is recorded as performing the task of drug discovery.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Precious3GPT — common questions
Precious3GPT— who created it?
It was published by Insilico Medicine AI,Harvard Medical School, based in Hong Kong, an organisation categorised as industry,Academia.
Precious3GPT— when was it released?
It was published in July 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.
Precious3GPT— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of drug discovery. These are the areas it was designed around; they describe intent rather than a hard boundary.
Precious3GPT— what GPU do I need to run it?
None. This 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.
Precious3GPT— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Precious3GPT— how many parameters does it have?
It has a parameter count of 89M. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
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.