Profile Job Results
Jobs
jgnn2vzmg
Results Ready
Name
efficientnet_b4
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, 380, 380, 3]Completion Time
9/5/2026, 9:11:37 PM
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-2026.08.28.1
Estimated Inference Time
9.99 ms
Estimated Peak Memory Usage
0 ‑ 50 MB
Compute Units
NPU
481
| Stage | Time | Memory |
|---|---|---|
First App Load | 4.95 s | 212 MB |
Subsequent App Load | 315 ms | 48‑49 MB |
Inference | 9.99 ms | 0‑50 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 |
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