Profile Job Results
Jobs
jgdvd6zeg
Results Ready
Name
unet_segmentation
Target Device
- SA7255P ADP
- Android 14
- Qualcomm® SA7255P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 640, 1280, 3]Completion Time
2/24/2026, 8:15:01 AM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.43.0.260127150333_193827
- QNN TfLite Delegate: v2.43.0.260127150333_193827
- Android: 14 (UAG2.240908.001)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00016-STD.PROD-3
- AI Hub: aihub-2026.02.14.0
Estimated Inference Time
954 ms
Estimated Peak Memory Usage
0 ‑ 325 MB
Compute Units
NPU
31
| Stage | Time | Memory |
|---|---|---|
First App Load | 1.54 min | 567‑576 MB |
Subsequent App Load | 908 ms | 53‑377 MB |
Inference | 954 ms | 0‑325 MB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.precision | kHtpFp16 |
| htp_options.optimization_strategy | kHtpOptimizeForInferenceO3 |
| htp_options.useConvHmx | true |
Sign up to run this model on a hosted Qualcomm® device!
Run on device