Micro-Star International Co., Ltd. MS-7D27
Geekbench AI Score
2568
Single Precision Score
3614
Half Precision Score
5495
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| User | Havok970 |
| Upload Date | September 29 2024 11:46 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics 770 (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D27 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z690 ACE (MS-7D27) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900 |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1682
312.8 IPS |
|
|
Image Classification (HP)
|
100% |
2834
527.0 IPS |
|
|
Image Classification (Q)
|
99% |
3872
722.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2558
41.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
4096
66.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
4863
78.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4646
5.42 IPS |
|
|
Pose Estimation (HP)
|
99% |
3389
3.95 IPS |
|
|
Pose Estimation (Q)
|
97% |
13918
16.3 IPS |
|
|
Object Detection (SP)
|
100% |
1512
119.9 IPS |
|
|
Object Detection (HP)
|
98% |
2456
195.4 IPS |
|
|
Object Detection (Q)
|
90% |
4402
352.0 IPS |
|
|
Face Detection (SP)
|
100% |
5339
63.4 IPS |
|
|
Face Detection (HP)
|
100% |
8147
96.8 IPS |
|
|
Face Detection (Q)
|
100% |
11010
130.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5393
41.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
8877
68.6 IPS |
|
|
Depth Estimation (Q)
|
89% |
12033
93.6 IPS |
|
|
Style Transfer (SP)
|
100% |
12181
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
18759
24.1 IPS |
|
|
Style Transfer (Q)
|
98% |
31612
40.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2157
79.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3498
129.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7141
264.4 IPS |
|
|
Text Classification (SP)
|
71% |
709
1.03 KIPS |
|
|
Text Classification (HP)
|
71% |
772
1.12 KIPS |
|
|
Text Classification (Q)
|
92% |
790
1.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
772
13.3 IPS |
|
|
Machine Translation (HP)
|
98% |
1076
18.6 IPS |
|
|
Machine Translation (Q)
|
100% |
922
15.9 IPS |
