Qualcomm IOT
Geekbench AI Score
122
Single Precision Score
97
Half Precision Score
87
Quantized Score
Geekbench AI 1.0.0 for Windows AArch64
Result Information
| Upload Date | August 26 2024 09:41 AM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | QNN |
| Device | |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | Qualcomm IOT |
| Motherboard | |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Pentium II/III |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARMv8 (64-bit) Family 8 Model D05 Revision 200 |
| Base Frequency | 2.71 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
159
29.5 IPS |
|
|
Image Classification (HP)
|
100% |
72
13.4 IPS |
|
|
Image Classification (Q)
|
100% |
96
17.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
92
1.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
99
1.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
98
1.59 IPS |
|
|
Pose Estimation (SP)
|
100% |
404
0.47 IPS |
|
|
Pose Estimation (HP)
|
100% |
227
0.27 IPS |
|
|
Pose Estimation (Q)
|
95% |
159
0.19 IPS |
|
|
Object Detection (SP)
|
100% |
42
3.29 IPS |
|
|
Object Detection (HP)
|
99% |
31
2.44 IPS |
|
|
Object Detection (Q)
|
89% |
34
2.68 IPS |
|
|
Face Detection (SP)
|
100% |
88
1.05 IPS |
|
|
Face Detection (HP)
|
100% |
51
0.61 IPS |
|
|
Face Detection (Q)
|
97% |
78
0.93 IPS |
|
|
Depth Estimation (SP)
|
100% |
102
0.78 IPS |
|
|
Depth Estimation (HP)
|
99% |
86
0.66 IPS |
|
|
Depth Estimation (Q)
|
73% |
91
0.74 IPS |
|
|
Style Transfer (SP)
|
100% |
508
0.65 IPS |
|
|
Style Transfer (HP)
|
100% |
423
0.54 IPS |
|
|
Style Transfer (Q)
|
98% |
291
0.38 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
76
2.82 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
90
3.31 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
66
2.46 IPS |
|
|
Text Classification (SP)
|
100% |
86
114.8 IPS |
|
|
Text Classification (HP)
|
100% |
68
90.7 IPS |
|
|
Text Classification (Q)
|
97% |
53
71.3 IPS |
|
|
Machine Translation (SP)
|
100% |
99
1.70 IPS |
|
|
Machine Translation (HP)
|
99% |
142
2.45 IPS |
|
|
Machine Translation (Q)
|
59% |
72
1.67 IPS |
