Mobile V-MoEs
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
- Apple
- Organisation type
- Industry
- Country
- United States of America
- Published
- 8 September 2023
- Authors
- Erik Daxberger, Floris Weers, Bowen Zhang, Tom Gunter, Ruoming Pang, Marcin Eichner, Michael Emmersberger, Yinfei Yang, Alexander Toshev, Xianzhi Du
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Image classification
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
- 62,720,000 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
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
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
- Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Mobile V-MoEs was published by Apple, in the country recorded as United States of America, during September 2023. The publishing organisation is categorised as industry.
It works in the domain of Vision, and is recorded as performing the task of image classification.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
The training set ran to roughly 62,720,000 tokens of text.
Answers
Mobile V-MoEs — common questions
Mobile V-MoEs— what is it used for?
It works in the domain of Vision, and is recorded as handling the task of image classification. 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.
Mobile V-MoEs— 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.
Mobile V-MoEs— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Mobile V-MoEs— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Mobile V-MoEs— who created it?
It was published by Apple, based in United States of America, an organisation categorised as industry.
Mobile V-MoEs— when was it released?
It was published in September 2023. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.