Micro-Star International Co., Ltd. MS-7D26
Geekbench AI Score
3694
Single Precision Score
4737
Half Precision Score
6951
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | danm1988 |
| Upload Date | April 17 2025 05:19 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Server GPU SG-18M (dGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D26 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z690 GODLIKE (MS-7D26) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900T |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 1.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2161
401.9 IPS |
|
|
Image Classification (HP)
|
100% |
2858
531.5 IPS |
|
|
Image Classification (Q)
|
99% |
3636
678.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
3355
54.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
4909
79.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
5308
86.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8433
9.84 IPS |
|
|
Pose Estimation (HP)
|
99% |
6183
7.21 IPS |
|
|
Pose Estimation (Q)
|
97% |
25575
29.9 IPS |
|
|
Object Detection (SP)
|
100% |
2200
174.5 IPS |
|
|
Object Detection (HP)
|
99% |
3046
242.3 IPS |
|
|
Object Detection (Q)
|
90% |
4678
374.0 IPS |
|
|
Face Detection (SP)
|
100% |
6001
71.3 IPS |
|
|
Face Detection (HP)
|
100% |
8872
105.4 IPS |
|
|
Face Detection (Q)
|
100% |
12675
150.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
8373
64.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12418
96.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
16618
129.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21669
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
29898
38.4 IPS |
|
|
Style Transfer (Q)
|
98% |
55493
71.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3491
128.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5269
194.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
9041
334.8 IPS |
|
|
Text Classification (SP)
|
71% |
888
1.28 KIPS |
|
|
Text Classification (HP)
|
71% |
1102
1.59 KIPS |
|
|
Text Classification (Q)
|
92% |
956
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
1043
18.0 IPS |
|
|
Machine Translation (HP)
|
97% |
1126
19.5 IPS |
|
|
Machine Translation (Q)
|
98% |
1129
19.5 IPS |
