Microsoft Corporation Surface Pro 9
Geekbench AI Score
4214
Single Precision Score
5463
Half Precision Score
8354
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | dynamiteCobra88 |
| Upload Date | November 26 2024 03:07 PM |
| Views | 26 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Iris(R) Xe Graphics (iGPU) |
| 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 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2482
461.6 IPS |
|
|
Image Classification (HP)
|
100% |
3568
663.6 IPS |
|
|
Image Classification (Q)
|
99% |
5031
938.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3817
61.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
5984
97.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
8530
138.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9609
11.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
7017
8.19 IPS |
|
|
Pose Estimation (Q)
|
97% |
28995
33.9 IPS |
|
|
Object Detection (SP)
|
100% |
2450
194.4 IPS |
|
|
Object Detection (HP)
|
100% |
3287
260.7 IPS |
|
|
Object Detection (Q)
|
90% |
4755
380.2 IPS |
|
|
Face Detection (SP)
|
100% |
6632
78.8 IPS |
|
|
Face Detection (HP)
|
100% |
9944
118.2 IPS |
|
|
Face Detection (Q)
|
100% |
14399
171.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
8938
68.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
13803
106.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
17311
134.6 IPS |
|
|
Style Transfer (SP)
|
100% |
24034
30.9 IPS |
|
|
Style Transfer (HP)
|
100% |
33465
43.0 IPS |
|
|
Style Transfer (Q)
|
98% |
63518
81.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3870
142.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5809
214.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
9898
366.6 IPS |
|
|
Text Classification (SP)
|
71% |
1204
1.74 KIPS |
|
|
Text Classification (HP)
|
71% |
1233
1.78 KIPS |
|
|
Text Classification (Q)
|
92% |
1232
1.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
1195
20.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1462
25.2 IPS |
|
|
Machine Translation (Q)
|
100% |
1451
25.0 IPS |
