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Jobs
jgd3j8zzp
Results Ready
Name
controlnet_canny_controlnet
Target Device
  • Arduino VENTUNO Q
  • Ubuntu 24.04
  • Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
text_emb: uint16[1, 77, 768]
image_cond: uint16[1, 512, 512, 3]
latent: uint16[1, 64, 64, 4]
timestep: uint16[1, 1]
Completion Time
9/5/2026, 8:50:42 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
70.3 ms
Estimated Peak Memory Usage
0 ‑ 17 MB
Compute Units
NPU
663
StageTimeMemory
First App Load
420 ms2 MB
Subsequent App Load
360 ms2 MB
Inference
70.3 ms0‑17 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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