Profile Job Results
Jobs
jgnk1o0vg
Results Ready
Name
nafnet_deblur
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, 360, 640, 3]Completion Time
8/9/2026, 12:03:39 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
75.2 ms
Estimated Peak Memory Usage
1 ‑ 80 MB
Compute Units
NPU
1480
| Stage | Time | Memory |
|---|---|---|
First App Load | 3.73 min | 866‑867 MB |
Subsequent App Load | 397 ms | 81‑83 MB |
Inference | 75.2 ms | 1‑80 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