Profile Job Results
Jobs
jp1jr7v7p
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
9/5/2026, 8:52:26 AM
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-2026.08.28.1
Estimated Inference Time
262 ms
Estimated Peak Memory Usage
0 ‑ 4 MB
Compute Units
NPU
171
| Stage | Time | Memory |
|---|---|---|
First App Load | 549 ms | 2 MB |
Subsequent App Load | 387 ms | 2 MB |
Inference | 262 ms | 0‑4 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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