NASNet: Optimized for Qualcomm Devices

NASNet is a vision transformer model that can classify images from the Imagenet dataset.

This is based on the implementation of NASNet found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime	Precision	Chipset	SDK Versions	Download
TFLITE	float	Universal	QAIRT 2.42, TFLite 2.17.0	Download

For more device-specific assets and performance metrics, visit NASNet on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

• Custom weights (e.g., fine-tuned checkpoints)
• Custom input shapes
• Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for NASNet on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

• Model checkpoint: nasnetalarge.tf_in1k
• Input resolution: 224x224
• GMACs: 5.9
• Activations (M): 19.4
• Number of parameters: 88.7M
• Model size (float): 338 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
NASNet	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	5.589 ms	0 - 671 MB	NPU
NASNet	TFLITE	float	Qualcomm® QCS8275 (Proxy)	36.767 ms	0 - 526 MB	NPU
NASNet	TFLITE	float	Qualcomm® QCS8550 (Proxy)	7.663 ms	0 - 3 MB	NPU
NASNet	TFLITE	float	Qualcomm® QCS9075	10.262 ms	0 - 191 MB	NPU
NASNet	TFLITE	float	Qualcomm® QCS8450 (Proxy)	23.477 ms	0 - 648 MB	NPU
NASNet	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	4.596 ms	0 - 524 MB	NPU
NASNet	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	4.11 ms	0 - 529 MB	NPU

License

• The license for the original implementation of NASNet can be found here.

References

• Learning Transferable Architectures for Scalable Image Recognition
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.