Micro-Star International Co., Ltd. MS-7D42
Geekbench ML Score
27432
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | December 05 2025 07:26 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Professionnel (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D42 |
| Motherboard | Micro-Star International Co., Ltd. MAG Z690M MORTAR WIFI (MS-7D42) |
| Power Plan | Utilisation normale |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700K |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 2.00 MB x 3 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
13354
2.50 KIPS |
|
|
Image Classification (F16)
|
100% |
13028
2.44 KIPS |
|
|
Image Classification (I8)
|
100% |
11419
2.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
18775
313.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
19068
318.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
17670
295.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
224163
271.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
227504
275.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
197894
239.6 IPS |
|
|
Object Detection (F32)
|
100% |
8393
626.6 IPS |
|
|
Object Detection (F16)
|
100% |
7071
527.9 IPS |
|
|
Object Detection (I8)
|
50% |
8018
598.6 IPS |
|
|
Face Detection (F32)
|
100% |
41000
487.5 IPS |
|
|
Face Detection (F16)
|
100% |
40412
480.5 IPS |
|
|
Face Detection (I8)
|
89% |
34756
413.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
88682
687.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
88697
687.8 IPS |
|
|
Depth Estimation (I8)
|
94% |
68159
528.6 IPS |
|
|
Style Transfer (F32)
|
100% |
330318
434.5 IPS |
|
|
Style Transfer (F16)
|
100% |
327995
431.4 IPS |
|
|
Style Transfer (I8)
|
98% |
294650
387.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
51809
1.85 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
48555
1.73 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
42600
1.52 KIPS |
|
|
Text Classification (F32)
|
100% |
3611
5.19 KIPS |
|
|
Text Classification (F16)
|
100% |
3595
5.17 KIPS |
|
|
Text Classification (I8)
|
98% |
2306
3.31 KIPS |
|
|
Machine Translation (F32)
|
100% |
5046
92.9 IPS |
|
|
Machine Translation (F16)
|
100% |
5027
92.5 IPS |
|
|
Machine Translation (I8)
|
70% |
2904
53.4 IPS |
