Profile Job Results
Jobs
jgnevermg
Results Ready
Name
efficientnet_b4_float
Target Device
- Snapdragon 8 Elite Gen 5 QRD
- Android 16
- Snapdragon® 8 Elite Gen 5 | SM8850
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
1/11/2026, 4:24:28 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: 16 (BQ2A.251016.001-BP2A.250605.031.A3)
- Build ID: Kaanapali.LA.1.0.r1-01040-STD.PROD-1
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
1.49 ms
Estimated Peak Memory Usage
0 ‑ 192 MB
Compute Units
NPU
482
| Stage | Time | Memory |
|---|---|---|
First App Load | 1.34 s | 722‑728 MB |
Subsequent App Load | 129 ms | 0‑191 MB |
Inference | 1.49 ms | 0‑192 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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