Profile Job Results
Jobs
jgneve3vg
Results Ready
Name
efficientnet_v2_s_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, 3:36:58 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
3.75 ms
Estimated Peak Memory Usage
0 ‑ 196 MB
Compute Units
NPU
508
| Stage | Time | Memory |
|---|---|---|
First App Load | 6.32 s | 456‑465 MB |
Subsequent App Load | 392 ms | 48‑244 MB |
Inference | 3.75 ms | 0‑196 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 |
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