Profile Job Results
Jobs
jp2wm40qp
Results Ready
Name
mediapipe_hand_gesture_canned_gesture_classifier
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
hand: uint8[1, 64]mirrored_hand: uint8[1, 64]Completion Time
8/22/2026, 7:16:10 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-2026.08.14.0
Estimated Inference Time
154 μs
Estimated Peak Memory Usage
0 ‑ 3 MB
Compute Units
NPU
99
| Stage | Time | Memory |
|---|---|---|
First App Load | 383 ms | 88‑89 MB |
Subsequent App Load | 162 ms | 2‑3 MB |
Inference | 154 μs | 0‑3 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