Profile Job Results
Jobs
j5q2q29m5
Results Ready
Name
efficientnet_b4_float
Target Device
- QCS8450 (Proxy)
- Android 13
- Qualcomm® QCS8450
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: float32[1, 224, 224, 3]Completion Time
1/11/2026, 3:22:07 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: 13 (TP1A.220624.014)
- AI Hub: aihub-2026.01.05.0
Estimated Inference Time
7.62 ms
Estimated Peak Memory Usage
0 ‑ 271 MB
Compute Units
NPU
482
| Stage | Time | Memory |
|---|---|---|
First App Load | 2.21 s | 611‑619 MB |
Subsequent App Load | 236 ms | 73‑344 MB |
Inference | 7.62 ms | 0‑271 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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