Profile Job Results
Jobs
j574zyml5
Results Ready
Name
ffnet_78s
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image: float32[1, 1024, 2048, 3]Completion Time
9/5/2026, 10:14:41 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
62.6 ms
Estimated Peak Memory Usage
0 ‑ 83 MB
Compute Units
NPU
151
| Stage | Time | Memory |
|---|---|---|
First App Load | 10.4 s | 365‑366 MB |
Subsequent App Load | 252 ms | 56‑57 MB |
Inference | 62.6 ms | 0‑83 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