Project AURIONAI Use-Cases Research & Innovation
TinyML

MobileNet v2

Model listed in Arm ML-Zoo, optimised for Arm IP (Cortex-A, Cortex-M, Mali, Ethos-U) in TensorFlow Lite format.

Levelmodel
ClassTinyML
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessunknown
Runs onmicrocontroller, mobile or NPU
Statusactive

Lineage

successor
MobileNet v1 to MobileNet v2: successor, high confidenceMobileNet v2 to MobileNet v3: successor, high confidenceMobileNet v3 to MobileNet v4: successor, high confidenceMobileNet v1MobileNet v1Google, Apr 2017MobileNet v2MobileNet v2MobileNet v3MobileNet v3Google, May 2019MobileNet v4MobileNet v4Google, Apr 2024
GoogleMobileNet v1 is the parent (successor)high confidencenotes
GoogleMobileNet v3 is a child (successor)high confidencenotes
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 4 models. Confidence and evidence are the notes' own.

R&D Topics

TinyML on microcontrollersproduced by

Identity

Developer
not in the notes
Family
not in the notes
Released
– sources
Weights published
–
Record checked
10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
not in the notes
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
text
Output
labels and boxes
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
unknown
Licence
not in the notes sources
Access routes
not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
microcontroller, mobile or NPU
Footprint
not in the notes
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. GitHub - Arm-Examples/ML-zoo github.com https://github.com/ARM-software/ML-zoo

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "MobileNet v2", https://aurion.semai.id/models/mobilenet-v2/, records of October 2026.