Microsoft Corporation Surface Pro X
Geekbench ML Score
633
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AArch64
Result Information
| User | Zuluman |
| Upload Date | July 25 2025 10:07 AM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Microsoft Corporation Surface Pro X |
| Motherboard | Microsoft Corporation Surface Pro X |
| Power Plan | Ausbalanciert |
| CPU Information | |
|---|---|
| Name | Microsoft SQ1 @ 3.0 GHz |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARMv8 (64-bit) Family 8 Model 805 Revision D0E |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Qualcomm(R) Adreno(TM) 680 GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
432
80.9 IPS |
|
|
Image Classification (F16)
|
100% |
427
79.9 IPS |
|
|
Image Classification (I8)
|
100% |
233
43.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
462
7.72 IPS |
|
|
Image Segmentation (F16)
|
100% |
464
7.74 IPS |
|
|
Image Segmentation (I8)
|
98% |
273
4.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
2536
3.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
2542
3.08 IPS |
|
|
Pose Estimation (I8)
|
100% |
1812
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
339
25.3 IPS |
|
|
Object Detection (F16)
|
100% |
348
26.0 IPS |
|
|
Object Detection (I8)
|
71% |
236
17.6 IPS |
|
|
Face Detection (F32)
|
100% |
829
9.85 IPS |
|
|
Face Detection (F16)
|
100% |
856
10.2 IPS |
|
|
Face Detection (I8)
|
93% |
394
4.68 IPS |
|
|
Depth Estimation (F32)
|
100% |
1703
13.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1729
13.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
979
7.59 IPS |
|
|
Style Transfer (F32)
|
100% |
3651
4.80 IPS |
|
|
Style Transfer (F16)
|
100% |
3652
4.80 IPS |
|
|
Style Transfer (I8)
|
98% |
2568
3.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1348
48.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1322
47.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
561
20.0 IPS |
|
|
Text Classification (F32)
|
100% |
152
218.0 IPS |
|
|
Text Classification (F16)
|
100% |
156
224.8 IPS |
|
|
Text Classification (I8)
|
98% |
89
127.6 IPS |
|
|
Machine Translation (F32)
|
100% |
382
7.03 IPS |
|
|
Machine Translation (F16)
|
100% |
384
7.07 IPS |
|
|
Machine Translation (I8)
|
65% |
161
2.96 IPS |
