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Riffusion

Profile Job Results

Jobs
jvgdve9eg
Results Ready
Name
riffusion_quantized_UNet_Quantized
Target Device
  • Samsung Galaxy S24
  • Android 14
  • Snapdragon® 8 Gen 3 | SM8650
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
input_1: uint16[1, 64, 64, 4]
input_2: uint16[1, 1280]
input_3: uint16[1, 77, 768]
Completion Time
5/21/2024, 5:17:50 PM
Versions
  • QNN: v2.22.0.240425235059_92863
  • QNN Backend API: 5.22.0
  • QNN Core API: 2.15.0
  • Android: 14 (UP1A.231005.007)
  • AI Hub: aihub-2024.05.15.0
Estimated Inference Time
90.2 ms
Estimated Peak Memory Usage
0 - 2 GB
Compute Units
NPU
4933
StageTimeMemory
First App Load
470 ms1-9 MB
Subsequent App Load
412 ms4-13 MB
Inference
90.2 ms0-2 GB
QNNValue
context_options.htp_options.performance_modeBURST
default_graph_options.htp_options.precisionFLOAT16

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