Profile Job Results
Jobs
jgolmzmxg
Results Ready
Name
bevformer
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image: float32[6, 3, 480, 800]use_prev_bev: float32[1]prev_bev: float32[1, 50, 50, 256]can_bus: float32[18]lidar2img: float32[1, 6, 4, 4]Completion Time
9/19/2026, 12:52:57 PM
Options
--qairt_version latestVersions
- ONNX Runtime: 1.27.1
- QAIRT: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.11.0
Estimated Inference Time
1.91 s
Estimated Peak Memory Usage
29 ‑ 62 MB
Compute Units
NPU
1293
| Stage | Time | Memory |
|---|---|---|
First App Load | 1.76 min | 1 GB |
Subsequent App Load | 704 ms | 89‑90 MB |
Inference | 1.91 s | 29‑62 MB |
| ONNX Runtime | Value |
|---|---|
| execution_mode | SEQUENTIAL |
| intra_op_num_threads | 0 |
| inter_op_num_threads | 0 |
| enable_memory_pattern | false |
| enable_cpu_memory_arena | false |
| graph_optimization_level | ENABLE_ALL |
| QNN Execution Provider | Value |
|---|---|
| htp_performance_mode | "burst" |
| htp_graph_finalization_optimization_mode | "3" |
| enable_htp_fp16_precision | "1" |
| capture_network_visualizations | false |
| context_priority | "normal" |
| offload_graph_io_quantization | "1" |
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