Microsoft Corporation Surface Pro 9
Geekbench ML Score
2151
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | dynamiteCobra88 |
| Upload Date | December 08 2024 12:31 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Microsoft Corporation Surface Pro 9 |
| Motherboard | Microsoft Corporation Surface Pro 9 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1255U |
| Topology | 1 Processor, 10 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 4 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 48.0 KB x 6 |
| L2 Cache | 1.25 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1081
202.3 IPS |
|
|
Image Classification (F16)
|
100% |
1088
203.5 IPS |
|
|
Image Classification (I8)
|
100% |
871
163.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1698
28.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1700
28.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1211
20.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
9953
12.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
9976
12.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
4988
6.04 IPS |
|
|
Object Detection (F32)
|
100% |
1166
87.0 IPS |
|
|
Object Detection (F16)
|
100% |
1178
88.0 IPS |
|
|
Object Detection (I8)
|
54% |
1001
74.7 IPS |
|
|
Face Detection (F32)
|
100% |
2299
27.3 IPS |
|
|
Face Detection (F16)
|
100% |
2308
27.4 IPS |
|
|
Face Detection (I8)
|
89% |
1538
18.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
5123
39.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
5139
39.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
3653
28.3 IPS |
|
|
Style Transfer (F32)
|
100% |
21380
28.1 IPS |
|
|
Style Transfer (F16)
|
100% |
22069
29.0 IPS |
|
|
Style Transfer (I8)
|
98% |
13712
18.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3047
108.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3117
111.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1326
47.4 IPS |
|
|
Text Classification (F32)
|
100% |
669
961.2 IPS |
|
|
Text Classification (F16)
|
100% |
693
996.4 IPS |
|
|
Text Classification (I8)
|
98% |
366
526.5 IPS |
|
|
Machine Translation (F32)
|
100% |
897
16.5 IPS |
|
|
Machine Translation (F16)
|
100% |
895
16.5 IPS |
|
|
Machine Translation (I8)
|
70% |
450
8.27 IPS |
