Micro-Star International Co., Ltd. MS-7E32
Geekbench AI Score
28091
Single Precision Score
48056
Half Precision Score
21999
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | August 10 2025 09:01 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| 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 | Vyven |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265 |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
10972
2.04 KIPS |
|
|
Image Classification (HP)
|
100% |
17985
3.34 KIPS |
|
|
Image Classification (Q)
|
100% |
9765
1.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21862
354.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
32739
530.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
19879
323.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
167928
195.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
469652
548.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
141546
165.8 IPS |
|
|
Object Detection (SP)
|
100% |
14974
1.19 KIPS |
|
|
Object Detection (HP)
|
100% |
24074
1.91 KIPS |
|
|
Object Detection (Q)
|
83% |
12816
1.04 KIPS |
|
|
Face Detection (SP)
|
100% |
41356
491.4 IPS |
|
|
Face Detection (HP)
|
100% |
58784
698.5 IPS |
|
|
Face Detection (Q)
|
97% |
34618
412.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
69568
536.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
124448
958.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
55357
441.8 IPS |
|
|
Style Transfer (SP)
|
100% |
234639
301.6 IPS |
|
|
Style Transfer (HP)
|
100% |
794106
1.02 KIPS |
|
|
Style Transfer (Q)
|
98% |
200131
258.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40708
1.50 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
72514
2.68 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
32357
1.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3222
4.30 KIPS |
|
|
Text Classification (HP)
|
100% |
3924
5.24 KIPS |
|
|
Text Classification (Q)
|
97% |
2154
2.89 KIPS |
|
|
Machine Translation (SP)
|
100% |
5731
98.7 IPS |
|
|
Machine Translation (HP)
|
100% |
5970
102.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2821
52.9 IPS |
