Profile Job Results
Jobs
jp0men7eg
Results Ready
Name
controlnet_canny_text_encoder
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
tokens: int32[1, 77]Completion Time
9/19/2026, 9:41:15 AM
Options
--qairt_version latestVersions
- QAIRT: v2.50.0.260828221209
- QNN Backend API: 5.50.0
- QNN Core API: 2.39.0
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.11.0
Estimated Inference Time
3.05 ms
Estimated Peak Memory Usage
0 ‑ 3 MB
Compute Units
NPU
449
| Stage | Time | Memory |
|---|---|---|
First App Load | 306 ms | 2‑3 MB |
Subsequent App Load | 216 ms | 2‑3 MB |
Inference | 3.05 ms | 0‑3 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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