Profile Job Results
Jobs
jgl4x28l5
Results Ready
Name
squeezenet1_1_quantized
Target Device
- SA8775P ADP
- Android 14
- Qualcomm® SA8775P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: uint8[1, 224, 224, 3]Completion Time
3/11/2025, 8:14:42 PM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.32.0.250228225014_116386-auto
- QNN TfLite Delegate: v2.32.0.250228225014_116386-auto
- Android: 14 (UQ1A.240205.002)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00011-STD.PROD-1.89321.2
- AI Hub: aihub-2025.03.06.0
Estimated Inference Time
454 μs
Estimated Peak Memory Usage
0 ‑ 12 MB
Compute Units
NPU
43
| Stage | Time | Memory |
|---|---|---|
First App Load | 992 ms | 26‑35 MB |
Subsequent App Load | 840 ms | 23‑42 MB |
Inference | 454 μs | 0‑12 MB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.precision | kHtpFp16 |
| htp_options.useConvHmx | true |
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