Micro-Star International Co., Ltd. MS-7D31
Geekbench ML Score
4189
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 24 2024 11:27 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D31 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z690 EDGE WIFI (MS-7D31) |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600KF |
| 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 |
| L1 Instruction Cache | 64.0 KB x 10 |
| L1 Data Cache | 32.0 KB x 10 |
| L2 Cache | 4.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2253
421.6 IPS |
|
|
Image Classification (F16)
|
100% |
2198
411.3 IPS |
|
|
Image Classification (I8)
|
99% |
4093
765.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
2001
33.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1963
32.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
2808
46.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
7002
8.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
7270
8.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
22177
26.9 IPS |
|
|
Object Detection (F32)
|
100% |
2167
161.8 IPS |
|
|
Object Detection (F16)
|
100% |
2261
168.8 IPS |
|
|
Object Detection (I8)
|
62% |
2117
158.1 IPS |
|
|
Face Detection (F32)
|
100% |
4535
53.9 IPS |
|
|
Face Detection (F16)
|
100% |
4489
53.4 IPS |
|
|
Face Detection (I8)
|
89% |
4980
59.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
8567
66.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
8359
64.8 IPS |
|
|
Depth Estimation (I8)
|
96% |
15811
122.6 IPS |
|
|
Style Transfer (F32)
|
100% |
17673
23.2 IPS |
|
|
Style Transfer (F16)
|
100% |
16694
22.0 IPS |
|
|
Style Transfer (I8)
|
98% |
24470
32.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3724
133.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3764
134.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5953
212.6 IPS |
|
|
Text Classification (F32)
|
100% |
1716
2.47 KIPS |
|
|
Text Classification (F16)
|
100% |
1761
2.53 KIPS |
|
|
Text Classification (I8)
|
98% |
513
736.7 IPS |
|
|
Machine Translation (F32)
|
100% |
2238
41.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2370
43.6 IPS |
|
|
Machine Translation (I8)
|
67% |
3099
57.0 IPS |
