Profile Job Results
Jobs
j57x3q1qg
Results Ready
Name
resnet50_float
Target Device
- SA7255P ADP
- Android 14
- Qualcomm® SA7255P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
1/10/2026, 9:31:40 PM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.41.0.251128145156_191518-auto
- QNN TfLite Delegate: v2.41.0.251128145156_191518-auto
- Android: 14 (UQ1A.240205.002)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00012-STD.PROD-5
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
10.6 ms
Estimated Peak Memory Usage
0 ‑ 166 MB
Compute Units
NPU
79
| Stage | Time | Memory |
|---|---|---|
First App Load | 7.05 s | 441‑450 MB |
Subsequent App Load | 649 ms | 50‑216 MB |
Inference | 10.6 ms | 0‑166 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 |
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