Profile Job Results
Jobs
jglkk008p
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
1/31/2026, 10:49:44 PM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.42.0.251225135753_193295
- QNN TfLite Delegate: v2.42.0.251225135753_193295
- Android: 14 (UAG2.240908.001)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00016-STD.PROD-3
- AI Hub: aihub-2026.01.22.0
Estimated Inference Time
10.6 ms
Estimated Peak Memory Usage
0 ‑ 82 MB
Compute Units
NPU
79
| Stage | Time | Memory |
|---|---|---|
First App Load | 7.42 s | 341‑350 MB |
Subsequent App Load | 609 ms | 28‑109 MB |
Inference | 10.6 ms | 0‑82 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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