Profile Job Results
Jobs
j57ddzeq5
Results Ready
Name
convnext_base_float
Target Device
- QCS8450 (Proxy)
- Android 13
- Qualcomm® QCS8450
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
2/1/2026, 12:07:18 PM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.42.0.251225135753_193295
- QNN TfLite Delegate: v2.42.0.251225135753_193295
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2026.01.22.0
Estimated Inference Time
19.7 ms
Estimated Peak Memory Usage
0 ‑ 330 MB
Compute Units
NPU
598
| Stage | Time | Memory |
|---|---|---|
First App Load | 6.33 s | 2 GB |
Subsequent App Load | 400 ms | 223‑553 MB |
Inference | 19.7 ms | 0‑330 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.optimization_strategy | kHtpOptimizeForInferenceO3 |
| htp_options.useConvHmx | true |
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