Micro-Star International Co., Ltd. MS-7D25
Geekbench ML Score
1315
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | May 22 2024 04:03 PM |
| Views | 1 |
System Information
| 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 DDR4(MS-7D25) |
| Power Plan | PS_3.3-2.7_32w_0.912 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600K |
| Topology | 1 Processor, 12 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics 770 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
614
114.9 IPS |
|
|
Image Classification (F16)
|
100% |
615
115.0 IPS |
|
|
Image Classification (I8)
|
100% |
508
95.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
908
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
923
15.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
714
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
5091
6.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
5042
6.11 IPS |
|
|
Pose Estimation (I8)
|
100% |
3360
4.07 IPS |
|
|
Object Detection (F32)
|
100% |
620
46.3 IPS |
|
|
Object Detection (F16)
|
100% |
615
45.9 IPS |
|
|
Object Detection (I8)
|
54% |
531
39.6 IPS |
|
|
Face Detection (F32)
|
100% |
1366
16.2 IPS |
|
|
Face Detection (F16)
|
100% |
1369
16.3 IPS |
|
|
Face Detection (I8)
|
89% |
977
11.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2847
22.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2842
22.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2203
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
10115
13.3 IPS |
|
|
Style Transfer (F16)
|
100% |
10316
13.6 IPS |
|
|
Style Transfer (I8)
|
98% |
7788
10.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1674
59.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1687
60.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
924
33.0 IPS |
|
|
Text Classification (F32)
|
100% |
665
956.3 IPS |
|
|
Text Classification (F16)
|
100% |
706
1.01 KIPS |
|
|
Text Classification (I8)
|
98% |
370
531.1 IPS |
|
|
Machine Translation (F32)
|
100% |
631
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
647
11.9 IPS |
|
|
Machine Translation (I8)
|
70% |
383
7.04 IPS |
