Profile Job Results
Jobs
jgjq379e5
Results Ready
Name
resnet50
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
8/9/2026, 3:05:01 AM
Versions
- Lite RT: 1.4.5
- QAIRT: v2.45.0.260326154327
- QNN TfLite Delegate: v2.45.0.260326154327
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.07.31.1
Estimated Inference Time
3.34 ms
Estimated Peak Memory Usage
0 ‑ 53 MB
Compute Units
NPU
79
| Stage | Time | Memory |
|---|---|---|
First App Load | 2.84 s | 191 MB |
Subsequent App Load | 219 ms | 51‑52 MB |
Inference | 3.34 ms | 0‑53 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