Micro-Star International Co., Ltd. MS-7E30
Geekbench AI Score
28167
Single Precision Score
48667
Half Precision Score
21948
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | September 03 2025 12:38 PM |
| Views | 2 |
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-7E30 |
| Motherboard | Micro-Star International Co., Ltd. B650M GAMING WIFI (MS-7E30) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 7600X |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 4.70 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11303
2.10 KIPS |
|
|
Image Classification (HP)
|
100% |
18900
3.51 KIPS |
|
|
Image Classification (Q)
|
100% |
10201
1.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
18809
304.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
27552
446.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
17844
290.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
167510
195.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
470937
549.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
144343
169.1 IPS |
|
|
Object Detection (SP)
|
100% |
15072
1.20 KIPS |
|
|
Object Detection (HP)
|
100% |
25188
2.00 KIPS |
|
|
Object Detection (Q)
|
83% |
12570
1.02 KIPS |
|
|
Face Detection (SP)
|
100% |
39981
475.1 IPS |
|
|
Face Detection (HP)
|
100% |
58577
696.0 IPS |
|
|
Face Detection (Q)
|
97% |
34045
405.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
69813
537.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
128821
992.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
54110
431.9 IPS |
|
|
Style Transfer (SP)
|
100% |
232843
299.3 IPS |
|
|
Style Transfer (HP)
|
100% |
785130
1.01 KIPS |
|
|
Style Transfer (Q)
|
98% |
198399
255.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
42161
1.56 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
77796
2.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
33267
1.23 KIPS |
|
|
Text Classification (SP)
|
100% |
3804
5.08 KIPS |
|
|
Text Classification (HP)
|
100% |
4562
6.09 KIPS |
|
|
Text Classification (Q)
|
97% |
2349
3.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
5620
96.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5739
98.9 IPS |
|
|
Machine Translation (Q)
|
70% |
2750
51.6 IPS |
