Profile Job Results
Jobs
jpr2j9ov5
Results Ready
Name
mediapipe_pose_float_PoseLandmarkDetector
Target Device
- SA8650 (Proxy)
- Android 13
- Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 256, 256, 3]Completion Time
10/4/2025, 10:36:32 PM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.38.0.250901140452_125126
- QNN TfLite Delegate: v2.38.0.250901140452_125126
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2025.09.26.0
Estimated Inference Time
807 μs
Estimated Peak Memory Usage
0 ‑ 81 MB
Compute Units
NPU
220
| Stage | Time | Memory |
|---|---|---|
First App Load | 947 ms | 116‑117 MB |
Subsequent App Load | 886 ms | 151‑154 MB |
Inference | 807 μs | 0‑81 MB |
| TensorFlow Lite | 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.useConvHmx | true |
Sign up to run this model on a hosted Qualcomm® device!
Run on device