Profile Job Results
Jobs
jgly79om5
Results Ready
Name
owl_vit
Target Device
- Arduino VENTUNO Q
- Ubuntu 24.04
- Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
pixel_values: float32[1, 3, 768, 768]input_ids: int32[1, 16]attention_mask: int32[1, 16]Completion Time
9/20/2026, 12:50:12 AM
Options
--qairt_version latestVersions
- Lite RT: 1.4.2
- QAIRT: v2.50.0.260828221209
- QNN TfLite Delegate: v2.50.0.260828221209
- Qualcomm Linux: 24.04
- AI Hub: aihub-2026.09.11.0
Estimated Inference Time
39.7 ms
Estimated Peak Memory Usage
0 ‑ 311 MB
Compute Units
NPU
1201
CPU
1
| Stage | Time | Memory |
|---|---|---|
First App Load | 48.1 s | 828‑829 MB |
Subsequent App Load | 508 ms | 304‑305 MB |
Inference | 39.7 ms | 0‑311 MB |
| Lite RT | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.performance_mode | kHtpBurst |
| htp_options.precision | kHtpFp16 |
| htp_options.optimization_strategy | kHtpOptimizeForInferenceO3 |
| htp_options.useConvHmx | true |
Sign up to run this model on a hosted Qualcomm® device!
Run on device