Microsoft Corporation Surface Pro 10 for Business
Geekbench ML Score
2132
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | dynamiteCobra88 |
| Upload Date | November 19 2024 04:37 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Microsoft Corporation Surface Pro 10 for Business |
| Motherboard | Microsoft Corporation Surface Pro 10 for Business |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 135U |
| Topology | 1 Processor, 12 Cores, 14 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 14 |
| L1 Data Cache | 32.0 KB x 14 |
| L2 Cache | 2.00 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
880
164.6 IPS |
|
|
Image Classification (F16)
|
100% |
803
150.3 IPS |
|
|
Image Classification (I8)
|
99% |
1875
350.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
880
14.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
642
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
2216
37.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
3345
4.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
3222
3.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
13193
16.0 IPS |
|
|
Object Detection (F32)
|
100% |
1004
75.0 IPS |
|
|
Object Detection (F16)
|
100% |
1037
77.4 IPS |
|
|
Object Detection (I8)
|
62% |
1225
91.5 IPS |
|
|
Face Detection (F32)
|
100% |
2426
28.8 IPS |
|
|
Face Detection (F16)
|
100% |
2390
28.4 IPS |
|
|
Face Detection (I8)
|
89% |
3115
37.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3896
30.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
3480
27.0 IPS |
|
|
Depth Estimation (I8)
|
96% |
8555
66.3 IPS |
|
|
Style Transfer (F32)
|
100% |
8750
11.5 IPS |
|
|
Style Transfer (F16)
|
100% |
8924
11.7 IPS |
|
|
Style Transfer (I8)
|
98% |
13234
17.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1399
50.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1028
36.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2973
106.2 IPS |
|
|
Text Classification (F32)
|
100% |
919
1.32 KIPS |
|
|
Text Classification (F16)
|
100% |
865
1.24 KIPS |
|
|
Text Classification (I8)
|
98% |
975
1.40 KIPS |
|
|
Machine Translation (F32)
|
100% |
1323
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1313
24.2 IPS |
|
|
Machine Translation (I8)
|
67% |
1951
35.9 IPS |
