Micro-Star International Co., Ltd. MS-7E49
Geekbench AI Score
9054
Single Precision Score
8946
Half Precision Score
21334
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | MrFox |
| Upload Date | December 10 2024 06:49 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 9 9950X 16-Core Processor |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E49 |
| Motherboard | Micro-Star International Co., Ltd. MPG X870E CARBON WIFI (MS-7E49) |
| Power Plan | Bitsum Highest Performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 9950X 16-Core Processor |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 5.50 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4943
919.3 IPS |
|
|
Image Classification (HP)
|
100% |
5381
1.00 KIPS |
|
|
Image Classification (Q)
|
100% |
12975
2.41 KIPS |
|
|
Image Segmentation (SP)
|
100% |
7293
118.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5967
96.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
13721
222.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
12567
14.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
12400
14.5 IPS |
|
|
Pose Estimation (Q)
|
98% |
47089
55.1 IPS |
|
|
Object Detection (SP)
|
100% |
5180
410.9 IPS |
|
|
Object Detection (HP)
|
100% |
5600
444.2 IPS |
|
|
Object Detection (Q)
|
88% |
19761
1.58 KIPS |
|
|
Face Detection (SP)
|
100% |
14927
177.4 IPS |
|
|
Face Detection (HP)
|
100% |
14602
173.5 IPS |
|
|
Face Detection (Q)
|
100% |
27839
330.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
15222
117.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
14135
108.9 IPS |
|
|
Depth Estimation (Q)
|
88% |
32416
252.2 IPS |
|
|
Style Transfer (SP)
|
100% |
33796
43.4 IPS |
|
|
Style Transfer (HP)
|
100% |
33887
43.6 IPS |
|
|
Style Transfer (Q)
|
98% |
124554
160.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7253
267.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7068
261.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
19182
710.4 IPS |
|
|
Text Classification (SP)
|
100% |
3902
5.21 KIPS |
|
|
Text Classification (HP)
|
100% |
4300
5.74 KIPS |
|
|
Text Classification (Q)
|
92% |
5998
8.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
7260
125.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6930
119.4 IPS |
|
|
Machine Translation (Q)
|
100% |
9118
157.1 IPS |
