Profile Job Results
Jobs
jp87y7w85
Results Ready
Name
efficientnet_b4_float
Target Device
- SA8775P ADP
- Android 14
- Qualcomm® SA8775P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
1/11/2026, 3:43:55 AM
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: Snapdragon_Auto.HQX.4.5.6.0.r2-00011-STD.PROD-1.89321.2
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
4.24 ms
Estimated Peak Memory Usage
0 ‑ 189 MB
Compute Units
NPU
482
| Stage | Time | Memory |
|---|---|---|
First App Load | 6.63 s | 513‑522 MB |
Subsequent App Load | 388 ms | 46‑235 MB |
Inference | 4.24 ms | 0‑189 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 |
| htp_options.device_id | 1 |
Sign up to run this model on a hosted Qualcomm® device!
Run on device