Qualcomm IOT
Geekbench ML Score
282
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AArch64
Result Information
| Upload Date | August 23 2024 06:31 AM |
| Views | 4 |
System Information
| 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 |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
76
14.2 IPS |
|
|
Image Classification (F16)
|
100% |
71
13.2 IPS |
|
|
Image Classification (I8)
|
99% |
357
66.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
111
1.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
111
1.85 IPS |
|
|
Image Segmentation (I8)
|
98% |
353
5.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
473
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
405
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
2076
2.51 IPS |
|
|
Object Detection (F32)
|
100% |
79
5.92 IPS |
|
|
Object Detection (F16)
|
100% |
84
6.27 IPS |
|
|
Object Detection (I8)
|
65% |
282
21.1 IPS |
|
|
Face Detection (F32)
|
100% |
210
2.49 IPS |
|
|
Face Detection (F16)
|
100% |
194
2.31 IPS |
|
|
Face Detection (I8)
|
89% |
665
7.91 IPS |
|
|
Depth Estimation (F32)
|
100% |
233
1.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
250
1.94 IPS |
|
|
Depth Estimation (I8)
|
96% |
1379
10.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1276
1.68 IPS |
|
|
Style Transfer (F16)
|
100% |
1251
1.65 IPS |
|
|
Style Transfer (I8)
|
98% |
3621
4.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
246
8.79 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
238
8.50 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
440
15.7 IPS |
|
|
Text Classification (F32)
|
100% |
175
250.8 IPS |
|
|
Text Classification (F16)
|
100% |
180
259.1 IPS |
|
|
Text Classification (I8)
|
98% |
84
121.0 IPS |
|
|
Machine Translation (F32)
|
100% |
156
2.87 IPS |
|
|
Machine Translation (F16)
|
100% |
149
2.74 IPS |
|
|
Machine Translation (I8)
|
67% |
277
5.09 IPS |
