Profile Job Results
Jobs
jp4v6e22p
Results Ready
Name
efficientvit_l2_cls_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
12/14/2025, 4:36:08 AM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.40.0.251030114326_189385
- QNN TfLite Delegate: v2.40.0.251030114326_189385
- Android: 16 (BQ2A.250705.001-BP2A.250605.031.A3)
- Build ID: Kaanapali.LA.1.0.r1-00850-STD.PROD-1
- AI Hub: aihub-2025.12.07.0
Estimated Inference Time
3.50 ms
Estimated Peak Memory Usage
0 ‑ 209 MB
Compute Units
NPU
349
| Stage | Time | Memory |
|---|---|---|
First App Load | 4.19 s | 1 GB |
Subsequent App Load | 4.15 s | 1‑2 GB |
Inference | 3.50 ms | 0‑209 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.useConvHmx | true |
Sign up to run this model on a hosted Qualcomm® device!
Run on device