Micro-Star International Co., Ltd. MS-7D75
Geekbench AI Score
48925
Single Precision Score
72934
Half Precision Score
35515
Quantized Score
Geekbench AI 1.3.0 Corporate for Windows AVX2
Result Information
| Upload Date | June 18 2025 07:00 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 IoT Enterprise LTSC (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D75 |
| Motherboard | Micro-Star International Co., Ltd. MAG B650 TOMAHAWK WIFI (MS-7D75) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 7950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 4.50 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
17244
3.21 KIPS |
|
|
Image Classification (HP)
|
100% |
22046
4.10 KIPS |
|
|
Image Classification (Q)
|
100% |
14767
2.75 KIPS |
|
|
Image Segmentation (SP)
|
100% |
39776
644.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
52741
855.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
36796
598.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
403798
471.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
960860
1.12 KIPS |
|
|
Pose Estimation (Q)
|
96% |
324993
380.7 IPS |
|
|
Object Detection (SP)
|
100% |
24885
1.97 KIPS |
|
|
Object Detection (HP)
|
100% |
32069
2.54 KIPS |
|
|
Object Detection (Q)
|
85% |
20271
1.63 KIPS |
|
|
Face Detection (SP)
|
100% |
76703
911.4 IPS |
|
|
Face Detection (HP)
|
100% |
104168
1.24 KIPS |
|
|
Face Detection (Q)
|
97% |
59772
712.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
107437
827.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
189724
1.46 KIPS |
|
|
Depth Estimation (Q)
|
77% |
75271
602.9 IPS |
|
|
Style Transfer (SP)
|
100% |
612524
787.4 IPS |
|
|
Style Transfer (HP)
|
100% |
1724525
2.22 KIPS |
|
|
Style Transfer (Q)
|
98% |
507806
654.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
73867
2.73 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
96275
3.55 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
51818
1.92 KIPS |
|
|
Text Classification (SP)
|
100% |
3929
5.24 KIPS |
|
|
Text Classification (HP)
|
100% |
4725
6.31 KIPS |
|
|
Text Classification (Q)
|
97% |
2349
3.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
7784
134.1 IPS |
|
|
Machine Translation (HP)
|
100% |
7668
132.1 IPS |
|
|
Machine Translation (Q)
|
70% |
3207
60.1 IPS |
