Profile Job Results
Jobs
jp4v6dq8p
Results Ready
Name
track_anything_float_TrackAnythingSegment
Target Device
- SA8650 (Proxy)
- Android 13
- Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
f16: float32[1, 1024, 20, 36]f8: float32[1, 512, 40, 72]f4: float32[1, 256, 80, 144]memory_readout: float32[1, 1, 512, 20, 36]hidden_state: float32[1, 1, 64, 20, 36]Completion Time
12/13/2025, 6:03:47 PM
Versions
- 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-2025.12.07.0
Estimated Inference Time
29.0 ms
Estimated Peak Memory Usage
2 ‑ 20 MB
Compute Units
NPU
120
| Stage | Time | Memory |
|---|---|---|
First App Load | 9.44 s | 484‑485 MB |
Subsequent App Load | 9.37 s | 514‑517 MB |
Inference | 29.0 ms | 2‑20 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