Micro-Star International Co., Ltd. MS-7C92
Geekbench AI Score
15123
Single Precision Score
25942
Half Precision Score
10356
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | April 04 2025 03:33 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3060 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7C92 |
| Motherboard | Micro-Star International Co., Ltd. MPG B550I GAMING EDGE WIFI (MS-7C92) |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 5600X |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 0 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6645
1.24 KIPS |
|
|
Image Classification (HP)
|
99% |
10931
2.04 KIPS |
|
|
Image Classification (Q)
|
99% |
4979
928.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
9959
161.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
15338
248.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
8053
130.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
74310
86.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
199252
232.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
61313
71.8 IPS |
|
|
Object Detection (SP)
|
100% |
7712
611.7 IPS |
|
|
Object Detection (HP)
|
100% |
13694
1.09 KIPS |
|
|
Object Detection (Q)
|
84% |
5998
483.7 IPS |
|
|
Face Detection (SP)
|
100% |
17689
210.2 IPS |
|
|
Face Detection (HP)
|
100% |
28862
342.9 IPS |
|
|
Face Detection (Q)
|
97% |
14145
168.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
36989
285.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
70964
548.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
25461
203.8 IPS |
|
|
Style Transfer (SP)
|
100% |
123233
158.4 IPS |
|
|
Style Transfer (HP)
|
100% |
316632
407.0 IPS |
|
|
Style Transfer (Q)
|
98% |
99071
127.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
22450
829.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
38071
1.41 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
14283
528.9 IPS |
|
|
Text Classification (SP)
|
100% |
2463
3.29 KIPS |
|
|
Text Classification (HP)
|
99% |
3223
4.30 KIPS |
|
|
Text Classification (Q)
|
97% |
1284
1.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3701
63.7 IPS |
|
|
Machine Translation (HP)
|
100% |
3793
65.3 IPS |
|
|
Machine Translation (Q)
|
70% |
1471
27.6 IPS |
