MobileNet
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
- Organisation type
- Industry
- Country
- United States of America
- Published
- 17 April 2017
- Authors
- AG Howard, M Zhu, B Chen, D Kalenichenko
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Object detection, Image classification, Face detection
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
- 4.2M
- Training data
- 1,280,000 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Citations
- 24,853
Sources
Where this record came from and when it was last checked.
- Reference
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
MobileNet was published by Google, in United States of America, in April 2017. It comes out of industry.
It works in Vision, and is recorded as doing object detection, Image classification, Face detection.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
Around 1,280,000 tokens went into training it.
Its inclusion criterion is highly cited.
Answers
MobileNet — common questions
Who created MobileNet?
MobileNet was published by Google, based in United States of America, categorised as industry.
When was MobileNet released?
MobileNet was published in April 2017. 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 MobileNet used for?
MobileNet works in Vision, and is recorded as handling object detection, Image classification, Face detection. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run MobileNet?
None. MobileNet 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 MobileNet open source?
The licensing for MobileNet was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does MobileNet have?
MobileNet has 4.2M 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.
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.