Profile Job Results
Jobs
jg9m40kl5
Results Ready
Name
bevdet_encoder
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image: float32[1, 18, 256, 704]Completion Time
8/22/2026, 1:52:54 PM
Versions
- QAIRT: v2.45.0.260326154327
- QNN Backend API: 5.45.0
- QNN Core API: 2.34.0
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.08.14.0
Estimated Inference Time
67.9 ms
Estimated Peak Memory Usage
12 ‑ 29 MB
Compute Units
NPU
141
| Stage | Time | Memory |
|---|---|---|
First App Load | 28.3 s | 418‑419 MB |
Subsequent App Load | 235 ms | 2 MB |
Inference | 67.9 ms | 12‑29 MB |
| QNN | Value |
|---|---|
| context_options.htp_options.performance_mode | BURST |
| default_graph_options.htp_options.optimizations[0].type | FINALIZE_OPTIMIZATION_FLAG |
| default_graph_options.htp_options.optimizations[0].value | 3.0 |
| default_graph_options.htp_options.precision | FLOAT16 |
| default_graph_options.htp_options.vtcm_size | 0 |
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