Micro-Star International Co., Ltd. MS-7E32
Geekbench AI Score
41454
Single Precision Score
59980
Half Precision Score
30702
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | September 04 2025 12:50 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E32 |
| Motherboard | Micro-Star International Co., Ltd. MAG Z890 TOMAHAWK WIFI (MS-7E32) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285K |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16018
2.98 KIPS |
|
|
Image Classification (HP)
|
100% |
20675
3.84 KIPS |
|
|
Image Classification (Q)
|
100% |
13349
2.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
25432
412.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
30172
489.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
24373
396.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
370490
432.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
821790
958.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
299641
351.0 IPS |
|
|
Object Detection (SP)
|
100% |
20679
1.64 KIPS |
|
|
Object Detection (HP)
|
100% |
25667
2.04 KIPS |
|
|
Object Detection (Q)
|
85% |
17457
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
56818
675.1 IPS |
|
|
Face Detection (HP)
|
100% |
70458
837.2 IPS |
|
|
Face Detection (Q)
|
97% |
46516
554.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
98680
760.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
177140
1.36 KIPS |
|
|
Depth Estimation (Q)
|
77% |
70946
568.2 IPS |
|
|
Style Transfer (SP)
|
100% |
558807
718.4 IPS |
|
|
Style Transfer (HP)
|
100% |
1491456
1.92 KIPS |
|
|
Style Transfer (Q)
|
98% |
465261
599.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
67944
2.51 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
88993
3.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
47363
1.75 KIPS |
|
|
Text Classification (SP)
|
100% |
4092
5.46 KIPS |
|
|
Text Classification (HP)
|
100% |
4985
6.65 KIPS |
|
|
Text Classification (Q)
|
97% |
2240
3.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
5512
94.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5547
95.5 IPS |
|
|
Machine Translation (Q)
|
70% |
2685
50.4 IPS |
