Profile Job Results
Jobs
jgjll8jxp
Results Ready
Name
efficientvit_l2_cls_float
Target Device
- SA7255P ADP
- Android 14
- Qualcomm® SA7255P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
2/1/2026, 6:41:02 AM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.42.0.251225135753_193295
- QNN TfLite Delegate: v2.42.0.251225135753_193295
- Android: 14 (UAG2.240908.001)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00016-STD.PROD-3
- AI Hub: aihub-2026.01.22.0
Estimated Inference Time
24.6 ms
Estimated Peak Memory Usage
0 ‑ 274 MB
Compute Units
NPU
349
| Stage | Time | Memory |
|---|---|---|
First App Load | 21.0 s | 1 GB |
Subsequent App Load | 959 ms | 132‑398 MB |
Inference | 24.6 ms | 0‑274 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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