Profile Job Results
Jobs
j568l0d0g
Results Ready
Name
controlnet_canny_vae
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
latent: uint16[1, 64, 64, 4]Completion Time
10/3/2026, 9:36:13 AM
Versions
- ONNX Runtime: 1.30.0
- QAIRT: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.25.0
Estimated Inference Time
211 ms
Estimated Peak Memory Usage
3 ‑ 7 MB
Compute Units
NPU
172
| Stage | Time | Memory |
|---|---|---|
First App Load | 388 ms | 68‑69 MB |
Subsequent App Load | 378 ms | 68‑69 MB |
Inference | 211 ms | 3‑7 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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