Profile Job Results

Jobs
jp27znmx5
Results Ready
Name
whisper_medium_decoder
Target Device
  • Snapdragon X2 Elite CRD
  • Windows 11
  • Snapdragon® X2 Elite | SC8480XP
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
input_ids: int32[1, 1]
position_ids: int32[1]
k_cache_self_0_in: float16[16, 1, 64, 199]
v_cache_self_0_in: float16[16, 1, 199, 64]
attention_mask: float16[1, 1, 1, 200]
k_cache_cross_0: float16[16, 1, 64, 1500]
v_cache_cross_0: float16[16, 1, 1500, 64]
k_cache_self_1_in: float16[16, 1, 64, 199]
v_cache_self_1_in: float16[16, 1, 199, 64]
k_cache_cross_1: float16[16, 1, 64, 1500]
v_cache_cross_1: float16[16, 1, 1500, 64]
k_cache_self_2_in: float16[16, 1, 64, 199]
v_cache_self_2_in: float16[16, 1, 199, 64]
k_cache_cross_2: float16[16, 1, 64, 1500]
v_cache_cross_2: float16[16, 1, 1500, 64]
k_cache_self_3_in: float16[16, 1, 64, 199]
v_cache_self_3_in: float16[16, 1, 199, 64]
k_cache_cross_3: float16[16, 1, 64, 1500]
v_cache_cross_3: float16[16, 1, 1500, 64]
k_cache_self_4_in: float16[16, 1, 64, 199]
v_cache_self_4_in: float16[16, 1, 199, 64]
k_cache_cross_4: float16[16, 1, 64, 1500]
v_cache_cross_4: float16[16, 1, 1500, 64]
k_cache_self_5_in: float16[16, 1, 64, 199]
v_cache_self_5_in: float16[16, 1, 199, 64]
k_cache_cross_5: float16[16, 1, 64, 1500]
v_cache_cross_5: float16[16, 1, 1500, 64]
k_cache_self_6_in: float16[16, 1, 64, 199]
v_cache_self_6_in: float16[16, 1, 199, 64]
k_cache_cross_6: float16[16, 1, 64, 1500]
v_cache_cross_6: float16[16, 1, 1500, 64]
k_cache_self_7_in: float16[16, 1, 64, 199]
v_cache_self_7_in: float16[16, 1, 199, 64]
k_cache_cross_7: float16[16, 1, 64, 1500]
v_cache_cross_7: float16[16, 1, 1500, 64]
k_cache_self_8_in: float16[16, 1, 64, 199]
v_cache_self_8_in: float16[16, 1, 199, 64]
k_cache_cross_8: float16[16, 1, 64, 1500]
v_cache_cross_8: float16[16, 1, 1500, 64]
k_cache_self_9_in: float16[16, 1, 64, 199]
v_cache_self_9_in: float16[16, 1, 199, 64]
k_cache_cross_9: float16[16, 1, 64, 1500]
v_cache_cross_9: float16[16, 1, 1500, 64]
k_cache_self_10_in: float16[16, 1, 64, 199]
v_cache_self_10_in: float16[16, 1, 199, 64]
k_cache_cross_10: float16[16, 1, 64, 1500]
v_cache_cross_10: float16[16, 1, 1500, 64]
k_cache_self_11_in: float16[16, 1, 64, 199]
v_cache_self_11_in: float16[16, 1, 199, 64]
k_cache_cross_11: float16[16, 1, 64, 1500]
v_cache_cross_11: float16[16, 1, 1500, 64]
k_cache_self_12_in: float16[16, 1, 64, 199]
v_cache_self_12_in: float16[16, 1, 199, 64]
k_cache_cross_12: float16[16, 1, 64, 1500]
v_cache_cross_12: float16[16, 1, 1500, 64]
k_cache_self_13_in: float16[16, 1, 64, 199]
v_cache_self_13_in: float16[16, 1, 199, 64]
k_cache_cross_13: float16[16, 1, 64, 1500]
v_cache_cross_13: float16[16, 1, 1500, 64]
k_cache_self_14_in: float16[16, 1, 64, 199]
v_cache_self_14_in: float16[16, 1, 199, 64]
k_cache_cross_14: float16[16, 1, 64, 1500]
v_cache_cross_14: float16[16, 1, 1500, 64]
k_cache_self_15_in: float16[16, 1, 64, 199]
v_cache_self_15_in: float16[16, 1, 199, 64]
k_cache_cross_15: float16[16, 1, 64, 1500]
v_cache_cross_15: float16[16, 1, 1500, 64]
k_cache_self_16_in: float16[16, 1, 64, 199]
v_cache_self_16_in: float16[16, 1, 199, 64]
k_cache_cross_16: float16[16, 1, 64, 1500]
v_cache_cross_16: float16[16, 1, 1500, 64]
k_cache_self_17_in: float16[16, 1, 64, 199]
v_cache_self_17_in: float16[16, 1, 199, 64]
k_cache_cross_17: float16[16, 1, 64, 1500]
v_cache_cross_17: float16[16, 1, 1500, 64]
k_cache_self_18_in: float16[16, 1, 64, 199]
v_cache_self_18_in: float16[16, 1, 199, 64]
k_cache_cross_18: float16[16, 1, 64, 1500]
v_cache_cross_18: float16[16, 1, 1500, 64]
k_cache_self_19_in: float16[16, 1, 64, 199]
v_cache_self_19_in: float16[16, 1, 199, 64]
k_cache_cross_19: float16[16, 1, 64, 1500]
v_cache_cross_19: float16[16, 1, 1500, 64]
k_cache_self_20_in: float16[16, 1, 64, 199]
v_cache_self_20_in: float16[16, 1, 199, 64]
k_cache_cross_20: float16[16, 1, 64, 1500]
v_cache_cross_20: float16[16, 1, 1500, 64]
k_cache_self_21_in: float16[16, 1, 64, 199]
v_cache_self_21_in: float16[16, 1, 199, 64]
k_cache_cross_21: float16[16, 1, 64, 1500]
v_cache_cross_21: float16[16, 1, 1500, 64]
k_cache_self_22_in: float16[16, 1, 64, 199]
v_cache_self_22_in: float16[16, 1, 199, 64]
k_cache_cross_22: float16[16, 1, 64, 1500]
v_cache_cross_22: float16[16, 1, 1500, 64]
k_cache_self_23_in: float16[16, 1, 64, 199]
v_cache_self_23_in: float16[16, 1, 199, 64]
k_cache_cross_23: float16[16, 1, 64, 1500]
v_cache_cross_23: float16[16, 1, 1500, 64]
Completion Time
4/18/2026, 9:01:41 AM
Versions
  • QAIRT: v2.45.0.260326154327
  • QNN Backend API: 5.45.0
  • QNN Core API: 2.34.0
  • Windows: Windows 11 (28000)
  • Build ID: APSS.WP_GL.1.0.c4-04500-SC8480XRELCSP4ZA-5
  • AI Hub: aihub-2026.04.13.0
Estimated Inference Time
18.8 ms
Estimated Peak Memory Usage
160 MB
Compute Units
NPU
5889
StageTimeMemory
First App Load
1.19 s34 MB
Subsequent App Load
1.14 s34 MB
Inference
18.8 ms160 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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