Profile Job Results
Jobs
jp2lrlj6g
Results Ready
Name
resnet50_float
Target Device
- SA8650 (Proxy)
- Android 13
- Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
11/30/2025, 12:14:38 AM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.40.0.251030114326_189385
- QNN TfLite Delegate: v2.40.0.251030114326_189385
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2025.11.18.0
Estimated Inference Time
2.28 ms
Estimated Peak Memory Usage
0 ‑ 358 MB
Compute Units
NPU
79
| Stage | Time | Memory |
|---|---|---|
First App Load | 2.24 s | 416‑418 MB |
Subsequent App Load | 2.23 s | 440‑442 MB |
Inference | 2.28 ms | 0‑358 MB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.performance_mode | kHtpBurst |
| htp_options.precision | kHtpFp16 |
| htp_options.useConvHmx | true |
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