Profile Job Results
Jobs
j5w96qjmp
Results Ready
Name
efficientvit_l2_cls_float
Target Device
- Samsung Galaxy S24
- Android 14
- Snapdragon® 8 Gen 3 | SM8650
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
1/11/2026, 4:44:06 AM
Options
--qairt_version latestVersions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.41.0.251128145156_191518
- QNN TfLite Delegate: v2.41.0.251128145156_191518
- Android: 14 (UP1A.231005.007)
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
5.32 ms
Estimated Peak Memory Usage
0 ‑ 430 MB
Compute Units
NPU
349
| Stage | Time | Memory |
|---|---|---|
First App Load | 4.65 s | 768‑775 MB |
Subsequent App Load | 194 ms | 132‑562 MB |
Inference | 5.32 ms | 0‑430 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.optimization_strategy | kHtpOptimizeForInferenceO3 |
| htp_options.useConvHmx | true |
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