Profile Job Results
Jobs
j5614y30p
Results Ready
Name
litehrnet_float
Target Device
- QCS8450 (Proxy)
- Android 13
- Qualcomm® QCS8450
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 3, 256, 192]Completion Time
1/11/2026, 12:23:17 AM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.41.0.251128145156_191518
- QNN TfLite Delegate: v2.41.0.251128145156_191518
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
5.32 ms
Estimated Peak Memory Usage
0 ‑ 215 MB
Compute Units
NPU
1110
CPU
2
| Stage | Time | Memory |
|---|---|---|
First App Load | 3.42 s | 200‑208 MB |
Subsequent App Load | 182 ms | 10‑225 MB |
Inference | 5.32 ms | 0‑215 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 |
Sign up to run this model on a hosted Qualcomm® device!
Run on device