Micro-Star International Co., Ltd. MS-7D09
Geekbench AI Score
2560
Single Precision Score
1263
Half Precision Score
3975
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 09 2024 08:56 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-11600 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D09 |
| Motherboard | Micro-Star International Co., Ltd. Z590-A PRO (MS-7D09) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-11600 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 167 Stepping 1 |
| Base Frequency | 2.81 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1616
300.4 IPS |
|
|
Image Classification (HP)
|
100% |
450
83.7 IPS |
|
|
Image Classification (Q)
|
99% |
3137
585.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1166
18.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
714
11.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2652
43.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5113
5.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
3965
4.63 IPS |
|
|
Pose Estimation (Q)
|
95% |
17640
20.7 IPS |
|
|
Object Detection (SP)
|
100% |
1654
131.2 IPS |
|
|
Object Detection (HP)
|
100% |
580
46.0 IPS |
|
|
Object Detection (Q)
|
88% |
1879
150.7 IPS |
|
|
Face Detection (SP)
|
100% |
1777
21.1 IPS |
|
|
Face Detection (HP)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (Q)
|
97% |
3678
43.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5381
41.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1799
13.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
6480
51.9 IPS |
|
|
Style Transfer (SP)
|
100% |
12174
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
9637
12.4 IPS |
|
|
Style Transfer (Q)
|
98% |
16030
20.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2306
85.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1989
73.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3631
134.4 IPS |
|
|
Text Classification (SP)
|
100% |
1734
2.32 KIPS |
|
|
Text Classification (HP)
|
100% |
745
994.9 IPS |
|
|
Text Classification (Q)
|
97% |
1498
2.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
1634
28.2 IPS |
|
|
Machine Translation (HP)
|
100% |
505
8.70 IPS |
|
|
Machine Translation (Q)
|
60% |
1722
38.4 IPS |
