Microsoft Corporation Surface Pro 9
Geekbench ML Score
1243
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AArch64
Result Information
| User | hmartinez82 |
| Upload Date | April 05 2024 07:17 AM |
| Views | 13 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | Microsoft Corporation Surface Pro 9 |
| Motherboard | Microsoft Corporation Surface Pro 9 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Microsoft SQ3 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARMv8 (64-bit) Family 8 Model D4B Revision 0 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Qualcomm(R) Adreno(TM) 8cx Gen 3 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
921
172.3 IPS |
|
|
Image Classification (F16)
|
100% |
921
172.3 IPS |
|
|
Image Classification (I8)
|
100% |
577
108.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1051
17.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1069
17.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
679
11.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
3971
4.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
3894
4.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
3379
4.09 IPS |
|
|
Object Detection (F32)
|
100% |
565
42.1 IPS |
|
|
Object Detection (F16)
|
100% |
569
42.5 IPS |
|
|
Object Detection (I8)
|
71% |
445
33.2 IPS |
|
|
Face Detection (F32)
|
100% |
2179
25.9 IPS |
|
|
Face Detection (F16)
|
100% |
2177
25.9 IPS |
|
|
Face Detection (I8)
|
93% |
1097
13.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3996
31.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
3978
30.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
2581
20.0 IPS |
|
|
Style Transfer (F32)
|
100% |
5563
7.32 IPS |
|
|
Style Transfer (F16)
|
100% |
5526
7.27 IPS |
|
|
Style Transfer (I8)
|
98% |
4736
6.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2706
96.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2710
96.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1548
55.3 IPS |
|
|
Text Classification (F32)
|
100% |
185
265.3 IPS |
|
|
Text Classification (F16)
|
100% |
181
260.0 IPS |
|
|
Text Classification (I8)
|
98% |
142
204.2 IPS |
|
|
Machine Translation (F32)
|
100% |
661
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
668
12.3 IPS |
|
|
Machine Translation (I8)
|
65% |
331
6.09 IPS |
