Profile Job Results
Jobs
jgk3mjrw5
Results Ready
Name
resnet_3d_float
Target Device
- SA8295P ADP
- Android 14
- Qualcomm® SA8295P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
video: float32[1, 16, 112, 112, 3]Completion Time
1/10/2026, 8:39:45 PM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.41.0.251128145156_191518-auto
- QNN TfLite Delegate: v2.41.0.251128145156_191518-auto
- Android: 14 (UQ1A.240205.002)
- Build ID: SA8295P.HQX.4.5.6.0-00006-STD.PROD-1
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
330 ms
Estimated Peak Memory Usage
0 ‑ 182 MB
Compute Units
NPU
57
| Stage | Time | Memory |
|---|---|---|
First App Load | 14.3 s | 870‑876 MB |
Subsequent App Load | 240 ms | 66‑248 MB |
Inference | 330 ms | 0‑182 MB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.precision | kHtpFp16 |
| htp_options.optimization_strategy | kHtpOptimizeForInferenceO3 |
| htp_options.useConvHmx | true |
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