Microsoft Corporation Surface Pro 9
Geekbench AI Score
4192
Single Precision Score
5498
Half Precision Score
8415
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | dynamiteCobra88 |
| Upload Date | November 25 2024 05:32 PM |
| Views | 2 |
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% |
2503
465.4 IPS |
|
|
Image Classification (HP)
|
100% |
3471
645.5 IPS |
|
|
Image Classification (Q)
|
99% |
5039
939.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
3841
62.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
6018
97.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
8435
136.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
9640
11.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
7032
8.21 IPS |
|
|
Pose Estimation (Q)
|
97% |
29050
34.0 IPS |
|
|
Object Detection (SP)
|
100% |
2467
195.7 IPS |
|
|
Object Detection (HP)
|
100% |
3328
264.0 IPS |
|
|
Object Detection (Q)
|
90% |
4788
382.9 IPS |
|
|
Face Detection (SP)
|
100% |
6674
79.3 IPS |
|
|
Face Detection (HP)
|
100% |
10081
119.8 IPS |
|
|
Face Detection (Q)
|
100% |
14460
171.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8960
69.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
13810
106.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
17552
136.5 IPS |
|
|
Style Transfer (SP)
|
100% |
24497
31.5 IPS |
|
|
Style Transfer (HP)
|
100% |
35000
45.0 IPS |
|
|
Style Transfer (Q)
|
98% |
63863
82.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3841
141.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5838
215.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
10144
375.7 IPS |
|
|
Text Classification (SP)
|
71% |
1089
1.58 KIPS |
|
|
Text Classification (HP)
|
71% |
1237
1.79 KIPS |
|
|
Text Classification (Q)
|
92% |
1259
1.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
1198
20.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1468
25.3 IPS |
|
|
Machine Translation (Q)
|
100% |
1456
25.1 IPS |
