Profile Job Results
Jobs
jgl39de8g
Results Ready
Name
bisenet_float
Target Device
- SA8650 (Proxy)
- Android 13
- Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 720, 960, 3]Completion Time
12/14/2025, 8:59:31 AM
Versions
- 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-2025.12.07.0
Estimated Inference Time
45.9 ms
Estimated Peak Memory Usage
32 ‑ 92 MB
Compute Units
NPU
65
| Stage | Time | Memory |
|---|---|---|
First App Load | 1.77 s | 270‑271 MB |
Subsequent App Load | 1.77 s | 307‑310 MB |
Inference | 45.9 ms | 32‑92 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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