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Profile Job Results

Jobs
j5w4yeq3g
Results Ready
Name
bevdet_decoder
Target Device
  • Arduino VENTUNO Q
  • Ubuntu 24.04
  • Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
bev_feature: float32[1, 64, 128, 128]
Completion Time
8/8/2026, 4:59:17 PM
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-2026.07.31.1
Estimated Inference Time
25.8 ms
Estimated Peak Memory Usage
4 ‑ 12 MB
Compute Units
NPU
73
StageTimeMemory
First App Load
2.20 s226‑227 MB
Subsequent App Load
172 ms2 MB
Inference
25.8 ms4‑12 MB
QNNValue
context_options.htp_options.performance_modeBURST
default_graph_options.htp_options.optimizations[0].typeFINALIZE_OPTIMIZATION_FLAG
default_graph_options.htp_options.optimizations[0].value3.0
default_graph_options.htp_options.precisionFLOAT16
default_graph_options.htp_options.vtcm_size0

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