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Qualcomm® AI Hub Models
RegNet-Y-800MF

Profile Job Results

Jobs
j567k9w0p
Results Ready
Name
regnet_y_800mf
Target Device
  • Arduino VENTUNO Q
  • Ubuntu 24.04
  • Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
image_tensor: float32[1, 224, 224, 3]
Completion Time
9/5/2026, 3:31:20 PM
Versions
  • Lite RT: 1.4.5
  • QAIRT: v2.45.0.260326154327
  • QNN TfLite Delegate: v2.45.0.260326154327
  • Qualcomm Linux: 24.04
  • AI Hub: aihub-2026.08.28.1
Estimated Inference Time
1.56 ms
Estimated Peak Memory Usage
0 ‑ 18 MB
Compute Units
NPU
140
StageTimeMemory
First App Load
2.34 s119 MB
Subsequent App Load
188 ms17‑18 MB
Inference
1.56 ms0‑18 MB
Lite RTValue
number_of_threads4
QNN DelegateValue
backend_typekHtpBackend
log_levelkLogLevelWarn
htp_options.performance_modekHtpBurst
htp_options.precisionkHtpFp16
htp_options.optimization_strategykHtpOptimizeForInferenceO3
htp_options.useConvHmxtrue

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