Micro-Star International Co., Ltd. MS-7E32
Geekbench AI Score
31500
Single Precision Score
53378
Half Precision Score
24388
Quantized Score
Geekbench AI 1.2.0 Corporate for Windows AVX2
Result Information
| User | boris_sdk |
| Upload Date | June 28 2025 06:44 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 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 | Atlas Power Scheme |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265K |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12706
2.36 KIPS |
|
|
Image Classification (HP)
|
100% |
21680
4.03 KIPS |
|
|
Image Classification (Q)
|
100% |
11532
2.14 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21036
341.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
29415
476.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
19140
311.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
188781
220.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
527131
615.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
162790
190.7 IPS |
|
|
Object Detection (SP)
|
100% |
16749
1.33 KIPS |
|
|
Object Detection (HP)
|
100% |
27343
2.17 KIPS |
|
|
Object Detection (Q)
|
83% |
13776
1.11 KIPS |
|
|
Face Detection (SP)
|
100% |
43181
513.1 IPS |
|
|
Face Detection (HP)
|
100% |
60753
721.9 IPS |
|
|
Face Detection (Q)
|
97% |
36848
439.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
78718
606.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
143408
1.10 KIPS |
|
|
Depth Estimation (Q)
|
78% |
61084
487.6 IPS |
|
|
Style Transfer (SP)
|
100% |
267478
343.8 IPS |
|
|
Style Transfer (HP)
|
100% |
883946
1.14 KIPS |
|
|
Style Transfer (Q)
|
98% |
228002
294.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
47196
1.74 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
84364
3.12 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37077
1.37 KIPS |
|
|
Text Classification (SP)
|
100% |
4289
5.72 KIPS |
|
|
Text Classification (HP)
|
100% |
5067
6.76 KIPS |
|
|
Text Classification (Q)
|
97% |
2655
3.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
6185
106.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6206
106.9 IPS |
|
|
Machine Translation (Q)
|
70% |
2977
55.8 IPS |
