µFormer
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
- Microsoft Research AI for Science
- Organisation type
- Industry
- Country
- United States of America
- Published
- 5 September 2024
- Authors
- Haoran Sun, Liang He, Pan Deng, Guoqing Liu, Haiguang Liu, Chuan Cao, Fusong Ju, Lijun Wu, Tao Qin, Tie-Yan Liu
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.
- Parameters
- 670M
- Training data
- 1,350,000,000 tokens
30,000,000 proteins × 300 amino acids/protein = 9,000,000,000 datapoints Total datapoints: 9.0e9
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
- Accelerating protein engineering with fitness landscape modeling and reinforcement learning
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
µFormer was published by Microsoft Research AI for Science, in United States of America, in September 2024. It comes out of industry.
It works in Biology, and is recorded as doing protein design.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training set ran to roughly 1,350,000,000 tokens.
Answers
µFormer — common questions
How many parameters does µFormer have?
µFormer has 670M parameters. 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.
Who created µFormer?
µFormer was published by Microsoft Research AI for Science, based in United States of America, categorised as industry.
When was µFormer released?
µFormer 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 µFormer used for?
µFormer works in Biology, and is recorded as handling protein design. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run µFormer?
None. µFormer 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 µFormer open source?
The licensing for µFormer 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.