Micro-Star International Co., Ltd. MS-7E22
Geekbench AI Score
8991
Single Precision Score
8418
Half Precision Score
13699
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | sure |
| Upload Date | April 10 2025 04:43 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285K |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise Insider Preview (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E22 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z890 ACE (MS-7E22) |
| Power Plan | High performance |
| 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% |
5407
1.01 KIPS |
|
|
Image Classification (HP)
|
100% |
5711
1.06 KIPS |
|
|
Image Classification (Q)
|
100% |
8502
1.58 KIPS |
|
|
Image Segmentation (SP)
|
100% |
7602
123.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
4262
69.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
9674
156.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
14328
16.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
11753
13.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
24621
28.8 IPS |
|
|
Object Detection (SP)
|
100% |
5189
411.6 IPS |
|
|
Object Detection (HP)
|
100% |
5761
457.0 IPS |
|
|
Object Detection (Q)
|
88% |
9509
762.2 IPS |
|
|
Face Detection (SP)
|
100% |
15656
186.0 IPS |
|
|
Face Detection (HP)
|
100% |
16094
191.2 IPS |
|
|
Face Detection (Q)
|
100% |
25095
298.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
14060
108.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
13974
107.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
25152
195.6 IPS |
|
|
Style Transfer (SP)
|
100% |
41262
53.0 IPS |
|
|
Style Transfer (HP)
|
100% |
33571
43.2 IPS |
|
|
Style Transfer (Q)
|
98% |
67328
86.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7769
286.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6813
251.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
13743
509.0 IPS |
|
|
Text Classification (SP)
|
100% |
4060
5.42 KIPS |
|
|
Text Classification (HP)
|
100% |
3116
4.16 KIPS |
|
|
Text Classification (Q)
|
92% |
5490
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3945
67.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6769
116.6 IPS |
|
|
Machine Translation (Q)
|
100% |
3772
65.0 IPS |
