Profile Job Results
Jobs
jgdn3vle5
Results Ready
Name
resnet_3d_quantized
Target Device
- SA7255P ADP
- Android 14
- Qualcomm® SA7255P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
video: uint8[1, 16, 112, 112, 3]Completion Time
3/11/2025, 10:07:21 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.r2-00012-STD.PROD-5
- AI Hub: aihub-2025.03.06.0
Estimated Inference Time
1.05 s
Estimated Peak Memory Usage
1 ‑ 48 MB
Compute Units
NPU
98
CPU
1
| Stage | Time | Memory |
|---|---|---|
First App Load | 34.5 s | 793‑803 MB |
Subsequent App Load | 35.4 s | 812‑879 MB |
Inference | 1.05 s | 1‑48 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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