Micro-Star International Co., Ltd. MS-7D25
Geekbench AI Score
34351
Single Precision Score
50105
Half Precision Score
26329
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | October 04 2025 10:21 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D25 |
| Motherboard | Micro-Star International Co., Ltd. PRO Z690-A (MS-7D25) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600K |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12930
2.40 KIPS |
|
|
Image Classification (HP)
|
99% |
18437
3.44 KIPS |
|
|
Image Classification (Q)
|
100% |
11281
2.10 KIPS |
|
|
Image Segmentation (SP)
|
100% |
23001
372.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
29345
475.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
20905
339.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
264032
308.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
510718
595.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
220626
258.5 IPS |
|
|
Object Detection (SP)
|
100% |
16426
1.30 KIPS |
|
|
Object Detection (HP)
|
100% |
23097
1.83 KIPS |
|
|
Object Detection (Q)
|
85% |
14197
1.14 KIPS |
|
|
Face Detection (SP)
|
100% |
47957
569.8 IPS |
|
|
Face Detection (HP)
|
100% |
61980
736.5 IPS |
|
|
Face Detection (Q)
|
97% |
40814
486.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
83239
641.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
150677
1.16 KIPS |
|
|
Depth Estimation (Q)
|
78% |
63344
505.8 IPS |
|
|
Style Transfer (SP)
|
100% |
380789
489.5 IPS |
|
|
Style Transfer (HP)
|
100% |
869170
1.12 KIPS |
|
|
Style Transfer (Q)
|
98% |
335971
433.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
54129
2.00 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
73976
2.73 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
40967
1.52 KIPS |
|
|
Text Classification (SP)
|
100% |
3708
4.95 KIPS |
|
|
Text Classification (HP)
|
99% |
4545
6.07 KIPS |
|
|
Text Classification (Q)
|
97% |
2250
3.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
5814
100.2 IPS |
|
|
Machine Translation (HP)
|
100% |
5726
98.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2707
50.8 IPS |
