Profile Job Results
Jobs
j57dd6kl5
Results Ready
Name
pidnet_float
Target Device
- QCS8450 (Proxy)
- Android 13
- Qualcomm® QCS8450
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 1024, 2048, 3]Completion Time
1/31/2026, 11:42:19 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
76.1 ms
Estimated Peak Memory Usage
3 ‑ 346 MB
Compute Units
NPU
169
| Stage | Time | Memory |
|---|---|---|
First App Load | 7.17 s | 372‑380 MB |
Subsequent App Load | 230 ms | 1‑343 MB |
Inference | 76.1 ms | 3‑346 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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