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Qualcomm® AI Hub Models
BEVDet

Profile Job Results

Jobs
j5m33x3dg
Results Ready
Name
bevdet_float
Target Device
  • SA8650 (Proxy)
  • Android 13
  • Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 18, 256, 704]
sensor2keyegos: float32[1, 6, 4, 4]
inv_intrins: float32[1, 6, 3, 3]
inv_post_rots: float32[1, 6, 3, 3]
post_trans: float32[1, 6, 1, 3]
Completion Time
10/26/2025, 4:51:05 AM
Options
--qairt_version latest --compute_unit cpu
Versions
  • TensorFlow Lite: 2.17.0
  • Android: 13 (TP1A.220624.014)
  • AI Hub: aihub-2025.10.21.0
Estimated Inference Time
1.89 s
Estimated Peak Memory Usage
126 ‑ 129 MB
Compute Units
CPU
492
StageTimeMemory
First App Load
457 ms547‑548 MB
Subsequent App Load
254 ms547‑555 MB
Inference
1.89 s126‑129 MB
TensorFlow LiteValue
number_of_threads4
XNNPACK DelegateValue

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