Profile Job Results
Jobs
j5m30vyqg
Results Ready
Name
mediapipe_pose_float_PoseLandmarkDetector
Target Device
- QCS8550 (Proxy)
- Android 12
- Qualcomm® QCS8550
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 256, 256, 3]Completion Time
11/29/2025, 9:43:44 PM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.40.0.251030114326_189385
- QNN TfLite Delegate: v2.40.0.251030114326_189385
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2025.11.18.0
Estimated Inference Time
824 μs
Estimated Peak Memory Usage
0 ‑ 78 MB
Compute Units
NPU
220
| Stage | Time | Memory |
|---|---|---|
First App Load | 961 ms | 179‑180 MB |
Subsequent App Load | 949 ms | 175‑178 MB |
Inference | 824 μs | 0‑78 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 |
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