Qualcomm® AI HubAI Hub

Profile Job Results

Jobs
jg9z8k3qp
Results Ready
Name
edgetam_memory_encoder
Target Device
  • Arduino VENTUNO Q
  • Ubuntu 24.04
  • Qualcomm® Dragonwing™ IQ-8275 | QCS8275
Creator
ai-hub-support@qti.qualcomm.com
Input Specs
pix_feat: uint8[1, 256, 64, 64]
mask_for_mem: uint8[1, 1, 1024, 1024]
Completion Time
9/19/2026, 5:22:20 PM
Options
--qairt_version latest
Versions
  • ONNX Runtime: 1.27.1
  • QAIRT: v2.50.0.260828221209
  • Qualcomm Linux: 24.04
  • AI Hub: aihub-2026.09.11.0
Estimated Inference Time
5.22 ms
Estimated Peak Memory Usage
2 ‑ 6 MB
Compute Units
NPU
250
StageTimeMemory
First App Load
12.0 s164‑165 MB
Subsequent App Load
403 ms14‑15 MB
Inference
5.22 ms2‑6 MB
ONNX RuntimeValue
execution_modeSEQUENTIAL
intra_op_num_threads0
inter_op_num_threads0
enable_memory_patternfalse
enable_cpu_memory_arenafalse
graph_optimization_levelENABLE_ALL
QNN Execution ProviderValue
htp_performance_mode"burst"
htp_graph_finalization_optimization_mode"3"
enable_htp_fp16_precision"1"
capture_network_visualizationsfalse
context_priority"normal"
offload_graph_io_quantization"1"

Sign up to run this model on a hosted Qualcomm® device!

Run on device