Micro-Star International Co., Ltd. MS-7E22
Geekbench AI Score
6529
Single Precision Score
2550
Half Precision Score
8012
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 24 2024 09:31 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285K |
| 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% |
3470
645.4 IPS |
|
|
Image Classification (HP)
|
100% |
814
151.4 IPS |
|
|
Image Classification (Q)
|
99% |
5819
1.09 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2875
46.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1627
26.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4749
77.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
17736
20.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
8617
10.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
56698
66.5 IPS |
|
|
Object Detection (SP)
|
100% |
4113
326.3 IPS |
|
|
Object Detection (HP)
|
100% |
1074
85.2 IPS |
|
|
Object Detection (Q)
|
88% |
3449
276.5 IPS |
|
|
Face Detection (SP)
|
100% |
6974
82.9 IPS |
|
|
Face Detection (HP)
|
100% |
2475
29.4 IPS |
|
|
Face Detection (Q)
|
97% |
6704
79.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
15544
119.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3676
28.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
14168
113.4 IPS |
|
|
Style Transfer (SP)
|
100% |
40216
51.7 IPS |
|
|
Style Transfer (HP)
|
100% |
22292
28.7 IPS |
|
|
Style Transfer (Q)
|
98% |
35216
45.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6200
228.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4012
148.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7770
287.7 IPS |
|
|
Text Classification (SP)
|
100% |
2207
2.95 KIPS |
|
|
Text Classification (HP)
|
100% |
1029
1.37 KIPS |
|
|
Text Classification (Q)
|
97% |
1951
2.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
3244
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1135
19.5 IPS |
|
|
Machine Translation (Q)
|
60% |
3980
88.8 IPS |
