MultiverSeg
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
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
- Massachusetts Institute of Technology (MIT),Databricks
- Organisation type
- Academia,Industry
- Country
- United States of America
- Published
- 31 August 2025
- Authors
- Hallee E. Wong, Jose Javier Gonzalez Ortiz, John Guttag, Adrian V. Dalca
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Biology, Medicine
- Task
- Image segmentation
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
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Open — downloadable
- Model access
- Open weights (unrestricted)
- Training code
- Unreleased
Apache 2.0 https://github.com/halleewong/MultiverSeg
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance
- Last updated
- 28 November 2025
What the numbers mean
Background
MultiverSeg was published by Massachusetts Institute of Technology (MIT),Databricks, in United States of America, in August 2025. The organisation is categorised as academia,Industry.
It works in Vision, Biology, Medicine, and is recorded as doing image segmentation.
The weights are published, so it can be downloaded and run on your own hardware indefinitely, offline, with no account attached.
Answers
MultiverSeg — common questions
Is MultiverSeg open source?
Its weights are published, so MultiverSeg can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
How many parameters does MultiverSeg have?
No parameter count has been published for MultiverSeg, which is why no memory or speed figure appears on this page.
Who created MultiverSeg?
MultiverSeg was published by Massachusetts Institute of Technology (MIT),Databricks, based in United States of America, categorised as academia,Industry.
When was MultiverSeg released?
MultiverSeg was published in August 2025.
What is MultiverSeg used for?
MultiverSeg works in Vision, Biology, Medicine, and is recorded as handling image segmentation. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Where can I download MultiverSeg?
The weights for MultiverSeg are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
What GPU do I need to run MultiverSeg?
We cannot say. MultiverSeg has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
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.