AlphaMut
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
- Indian Institute of Science Education and Research
- Organisation type
- Government
- Country
- India
- Published
- 24 September 2024
- Authors
- Prathith Bhargav, Arnab Mukherjee
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Mutation 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
New estimate: Helix-only: 1874*30=56220 Helix-in-protein: 32775*15=491625 Old estimate: Total Data Points = Helix-only Training Steps + Helix-in-protein Training Steps 168,000 + 190,000 = 358,000 = 3.58e5 datapoints
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
- AlphaMut: a deep reinforcement learning model to suggest helix-disrupting mutations
- Last updated
- 28 November 2025
What the numbers mean
Background
AlphaMut was published by Indian Institute of Science Education and Research, in India, in September 2024. The organisation is categorised as government.
It works in Biology, and is recorded as doing mutation prediction.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
AlphaMut — common questions
How many parameters does AlphaMut have?
No parameter count has been published for AlphaMut, which is why no memory or speed figure appears on this page.
Who created AlphaMut?
AlphaMut was published by Indian Institute of Science Education and Research, based in India, categorised as government.
When was AlphaMut released?
AlphaMut 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 AlphaMut used for?
AlphaMut works in Biology, and is recorded as handling mutation 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 AlphaMut?
None. AlphaMut 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 AlphaMut open source?
The licensing for AlphaMut 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.