Profile Job Results
Jobs
jglwnvqlp
Results Ready
Name
u2net_segmentation
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image: uint8[1, 320, 320, 3]Completion Time
10/20/2026, 8:49:48 AM
Options
--qairt_version 2.50Versions
- Lite RT: 1.4.2
- QAIRT: v2.50.0.260828221209
- QNN TfLite Delegate: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.10.10.0
Estimated Inference Time
6.53 ms
Estimated Peak Memory Usage
0 ‑ 47 MB
Compute Units
NPU
341
| Stage | Time | Memory |
|---|---|---|
First App Load | 6.41 s | 224‑225 MB |
Subsequent App Load | 293 ms | 46‑47 MB |
Inference | 6.53 ms | 0‑47 MB |
| Lite RT | 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