Micro-Star International Co., Ltd. MS-7D85
Geekbench AI Score
27901
Single Precision Score
57807
Half Precision Score
63199
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | danm1988 |
| Upload Date | September 22 2025 11:53 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Pro B60 Graphics (dGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D85 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z790 GODLIKE (MS-7D85) |
| Power Plan | Ultimate Performance |
| 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 | 256.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15603
2.90 KIPS |
|
|
Image Classification (HP)
|
100% |
31173
5.80 KIPS |
|
|
Image Classification (Q)
|
100% |
36523
6.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
29821
483.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
54240
879.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
56744
919.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
87721
102.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
368698
430.2 IPS |
|
|
Pose Estimation (Q)
|
97% |
712555
834.2 IPS |
|
|
Object Detection (SP)
|
100% |
12312
976.6 IPS |
|
|
Object Detection (HP)
|
100% |
32950
2.61 KIPS |
|
|
Object Detection (Q)
|
88% |
31149
2.50 KIPS |
|
|
Face Detection (SP)
|
100% |
34678
412.0 IPS |
|
|
Face Detection (HP)
|
100% |
64256
763.5 IPS |
|
|
Face Detection (Q)
|
100% |
70397
836.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
63477
489.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
146384
1.13 KIPS |
|
|
Depth Estimation (Q)
|
89% |
175541
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
200350
257.6 IPS |
|
|
Style Transfer (HP)
|
100% |
631073
811.3 IPS |
|
|
Style Transfer (Q)
|
98% |
695064
896.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
35010
1.29 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
83768
3.09 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84905
3.14 KIPS |
|
|
Text Classification (SP)
|
100% |
6552
8.75 KIPS |
|
|
Text Classification (HP)
|
100% |
6064
8.09 KIPS |
|
|
Text Classification (Q)
|
92% |
4366
5.87 KIPS |
|
|
Machine Translation (SP)
|
100% |
5625
96.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6728
115.9 IPS |
|
|
Machine Translation (Q)
|
100% |
6941
119.6 IPS |
