Micro-Star International Co., Ltd. MS-7E22
Geekbench AI Score
8403
Single Precision Score
9464
Half Precision Score
13589
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 24 2024 09:49 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E22 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z890 ACE (MS-7E22) |
| Power Plan | Prestazioni eccellenti |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 48.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5950
1.11 KIPS |
|
|
Image Classification (HP)
|
100% |
6740
1.25 KIPS |
|
|
Image Classification (Q)
|
56% |
6120
1.71 KIPS |
|
|
Image Segmentation (SP)
|
100% |
6546
106.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2805
45.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
3728
60.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
14975
17.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
34155
39.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
73834
86.5 IPS |
|
|
Object Detection (SP)
|
100% |
5501
436.4 IPS |
|
|
Object Detection (HP)
|
100% |
5845
463.7 IPS |
|
|
Object Detection (Q)
|
87% |
9308
747.0 IPS |
|
|
Face Detection (SP)
|
100% |
16146
191.9 IPS |
|
|
Face Detection (HP)
|
100% |
15867
188.5 IPS |
|
|
Face Detection (Q)
|
100% |
25592
304.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
15438
118.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
18307
141.0 IPS |
|
|
Depth Estimation (Q)
|
88% |
34602
269.2 IPS |
|
|
Style Transfer (SP)
|
100% |
44201
56.8 IPS |
|
|
Style Transfer (HP)
|
100% |
52850
67.9 IPS |
|
|
Style Transfer (Q)
|
98% |
96987
125.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8999
332.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13835
510.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22239
823.6 IPS |
|
|
Text Classification (SP)
|
100% |
1992
2.66 KIPS |
|
|
Text Classification (HP)
|
100% |
2170
2.90 KIPS |
|
|
Text Classification (Q)
|
92% |
2165
2.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
2770
47.7 IPS |
|
|
Machine Translation (HP)
|
100% |
3314
57.1 IPS |
|
|
Machine Translation (Q)
|
100% |
3313
57.1 IPS |
