Profile Job Results
Jobs
jpyonq3l5
Results Ready
Name
edgetam_encoder
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, 1024, 1024, 3]unnorm_coords: uint8[1, 2, 2]labels: uint8[1, 2]Completion Time
9/19/2026, 5:08:14 PM
Options
--qairt_version latestVersions
- Lite RT: 1.4.2
- QAIRT: v2.50.0.260828221209
- QNN TfLite Delegate: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.11.0
Estimated Inference Time
6.61 ms
Estimated Peak Memory Usage
5 ‑ 23 MB
Compute Units
NPU
305
| Stage | Time | Memory |
|---|---|---|
First App Load | 11.8 s | 227 MB |
Subsequent App Load | 261 ms | 10‑11 MB |
Inference | 6.61 ms | 5‑23 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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