FFNet-40S: Optimized for Qualcomm Devices

FFNet-40S is a "fuss-free network" that segments street scene images with per-pixel classes like road, sidewalk, and pedestrian. Trained on the Cityscapes dataset.

This is based on the implementation of FFNet-40S 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
ONNX	float	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	Download
ONNX	w8a8	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	Download
QNN_DLC	float	Universal	QAIRT 2.45	Download
QNN_DLC	w8a8	Universal	QAIRT 2.45	Download
TFLITE	float	Universal	QAIRT 2.45	Download
TFLITE	w8a8	Universal	QAIRT 2.45	Download

For more device-specific assets and performance metrics, visit FFNet-40S 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 FFNet-40S on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.semantic_segmentation

Model Stats:

• Model checkpoint: ffnet40S_dBBB_cityscapes_state_dict_quarts
• Input resolution: 2048x1024
• Number of output classes: 19
• Number of parameters: 13.9M
• Model size (float): 53.1 MB
• Model size (w8a8): 13.5 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
FFNet-40S	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	12.367 ms	13 - 234 MB	NPU
FFNet-40S	ONNX	float	Snapdragon® X2 Elite	13.428 ms	22 - 22 MB	NPU
FFNet-40S	ONNX	float	Snapdragon® X Elite	31.615 ms	24 - 24 MB	NPU
FFNet-40S	ONNX	float	Snapdragon® 8 Gen 3 Mobile	22.552 ms	29 - 304 MB	NPU
FFNet-40S	ONNX	float	Qualcomm® QCS8550 (Proxy)	32.116 ms	24 - 27 MB	NPU
FFNet-40S	ONNX	float	Qualcomm® QCS9075	47.946 ms	24 - 27 MB	NPU
FFNet-40S	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	15.648 ms	7 - 208 MB	NPU
FFNet-40S	ONNX	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	6.541 ms	2 - 197 MB	NPU
FFNet-40S	ONNX	w8a8	Snapdragon® X2 Elite	6.9 ms	9 - 9 MB	NPU
FFNet-40S	ONNX	w8a8	Snapdragon® X Elite	10.478 ms	8 - 8 MB	NPU
FFNet-40S	ONNX	w8a8	Snapdragon® 8 Gen 3 Mobile	6.545 ms	7 - 250 MB	NPU
FFNet-40S	ONNX	w8a8	Qualcomm® QCS6490	362.326 ms	202 - 239 MB	CPU
FFNet-40S	ONNX	w8a8	Qualcomm® QCS8550 (Proxy)	9.789 ms	0 - 26 MB	NPU
FFNet-40S	ONNX	w8a8	Qualcomm® QCS9075	12.939 ms	6 - 9 MB	NPU
FFNet-40S	ONNX	w8a8	Qualcomm® QCM6690	367.564 ms	230 - 239 MB	CPU
FFNet-40S	ONNX	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	7.725 ms	1 - 194 MB	NPU
FFNet-40S	ONNX	w8a8	Snapdragon® 7 Gen 4 Mobile	360.556 ms	169 - 178 MB	CPU
FFNet-40S	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	12.62 ms	24 - 263 MB	NPU
FFNet-40S	QNN_DLC	float	Snapdragon® X2 Elite	14.624 ms	24 - 24 MB	NPU
FFNet-40S	QNN_DLC	float	Snapdragon® X Elite	37.519 ms	24 - 24 MB	NPU
FFNet-40S	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	24.881 ms	0 - 268 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	135.577 ms	24 - 219 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	36.528 ms	24 - 26 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® SA8775P	48.892 ms	24 - 219 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® QCS9075	62.187 ms	24 - 52 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	63.5 ms	24 - 288 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® SA7255P	135.577 ms	24 - 219 MB	NPU
FFNet-40S	QNN_DLC	float	Qualcomm® SA8295P	53.694 ms	24 - 223 MB	NPU
FFNet-40S	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	18.242 ms	22 - 245 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	5.238 ms	6 - 232 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® X2 Elite	6.149 ms	6 - 6 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® X Elite	15.897 ms	6 - 6 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® 8 Gen 3 Mobile	10.494 ms	6 - 251 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCS6490	67.473 ms	6 - 14 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCS8275 (Proxy)	32.925 ms	6 - 203 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCS8550 (Proxy)	15.134 ms	6 - 33 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® SA8775P	15.684 ms	6 - 203 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCS9075	18.528 ms	6 - 14 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCM6690	126.872 ms	6 - 238 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® QCS8450 (Proxy)	21.473 ms	6 - 252 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® SA7255P	32.925 ms	6 - 203 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Qualcomm® SA8295P	20.051 ms	6 - 203 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	7.086 ms	6 - 217 MB	NPU
FFNet-40S	QNN_DLC	w8a8	Snapdragon® 7 Gen 4 Mobile	19.337 ms	6 - 223 MB	NPU
FFNet-40S	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	12.623 ms	2 - 252 MB	NPU
FFNet-40S	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	24.979 ms	2 - 303 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® QCS8275 (Proxy)	135.665 ms	2 - 210 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® QCS8550 (Proxy)	36.208 ms	2 - 5 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® SA8775P	48.985 ms	2 - 210 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® QCS9075	62.379 ms	0 - 56 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® QCS8450 (Proxy)	63.678 ms	3 - 303 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® SA7255P	135.665 ms	2 - 210 MB	NPU
FFNet-40S	TFLITE	float	Qualcomm® SA8295P	53.691 ms	2 - 217 MB	NPU
FFNet-40S	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	18.087 ms	1 - 239 MB	NPU
FFNet-40S	TFLITE	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	2.905 ms	0 - 224 MB	NPU
FFNet-40S	TFLITE	w8a8	Snapdragon® 8 Gen 3 Mobile	5.455 ms	1 - 249 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCS6490	52.01 ms	1 - 23 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCS8275 (Proxy)	20.065 ms	1 - 196 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCS8550 (Proxy)	7.509 ms	1 - 4 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® SA8775P	8.219 ms	1 - 197 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCS9075	9.582 ms	1 - 23 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCM6690	98.38 ms	1 - 231 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® QCS8450 (Proxy)	12.372 ms	0 - 246 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® SA7255P	20.065 ms	1 - 196 MB	NPU
FFNet-40S	TFLITE	w8a8	Qualcomm® SA8295P	11.697 ms	1 - 200 MB	NPU
FFNet-40S	TFLITE	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	3.992 ms	0 - 208 MB	NPU
FFNet-40S	TFLITE	w8a8	Snapdragon® 7 Gen 4 Mobile	11.552 ms	1 - 216 MB	NPU

License

• The license for the original implementation of FFNet-40S can be found here.

References

• Simple and Efficient Architectures for Semantic Segmentation
• 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.