Profile Job Results
Jobs
jp0o02w6p
Results Ready
Name
bevdet_encoder
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, 18, 256, 704]Completion Time
10/3/2026, 3:31:56 PM
Versions
- Lite RT: 1.4.2
- QAIRT: v2.50.0.260828221209
- QNN TfLite Delegate: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.25.0
Estimated Inference Time
68.7 ms
Estimated Peak Memory Usage
25 ‑ 115 MB
Compute Units
NPU
93
CPU
1
| Stage | Time | Memory |
|---|---|---|
First App Load | 19.7 s | 396‑397 MB |
Subsequent App Load | 364 ms | 52‑53 MB |
Inference | 68.7 ms | 25‑115 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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