Micro-Star International Co., Ltd. MS-7D28
Geekbench AI Score
5780
Single Precision Score
2014
Half Precision Score
6707
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Adam33k |
| Upload Date | October 11 2024 06:36 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) i9-14900KS |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D28 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z690 UNIFY-X (MS-7D28) |
| Power Plan | Zrwnowaony |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) i9-14900KS |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3056
568.3 IPS |
|
|
Image Classification (HP)
|
100% |
711
132.2 IPS |
|
|
Image Classification (Q)
|
99% |
5202
970.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2809
45.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1540
25.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4348
70.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
13551
15.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
5396
6.30 IPS |
|
|
Pose Estimation (Q)
|
95% |
42495
49.8 IPS |
|
|
Object Detection (SP)
|
100% |
3909
310.0 IPS |
|
|
Object Detection (HP)
|
100% |
938
74.4 IPS |
|
|
Object Detection (Q)
|
88% |
3094
248.0 IPS |
|
|
Face Detection (SP)
|
100% |
7105
84.4 IPS |
|
|
Face Detection (HP)
|
100% |
2396
28.5 IPS |
|
|
Face Detection (Q)
|
97% |
6836
81.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
13316
102.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2774
21.4 IPS |
|
|
Depth Estimation (Q)
|
77% |
14206
113.7 IPS |
|
|
Style Transfer (SP)
|
100% |
31422
40.4 IPS |
|
|
Style Transfer (HP)
|
100% |
14184
18.2 IPS |
|
|
Style Transfer (Q)
|
98% |
37282
48.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5235
193.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2502
92.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6812
252.2 IPS |
|
|
Text Classification (SP)
|
100% |
2137
2.85 KIPS |
|
|
Text Classification (HP)
|
100% |
940
1.25 KIPS |
|
|
Text Classification (Q)
|
97% |
749
1.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
2754
47.4 IPS |
|
|
Machine Translation (HP)
|
100% |
896
15.4 IPS |
|
|
Machine Translation (Q)
|
60% |
3358
74.9 IPS |
