Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
2836
Single Precision Score
4142
Half Precision Score
6488
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 19 2025 12:37 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics 770 (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-CF05 |
| Motherboard | Micro-Star International Co., Ltd. MS-CF05 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900K |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1765
328.3 IPS |
|
|
Image Classification (HP)
|
100% |
2901
539.5 IPS |
|
|
Image Classification (Q)
|
99% |
4401
820.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2536
41.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
4163
67.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
4932
80.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4503
5.25 IPS |
|
|
Pose Estimation (HP)
|
99% |
3279
3.83 IPS |
|
|
Pose Estimation (Q)
|
97% |
13461
15.8 IPS |
|
|
Object Detection (SP)
|
100% |
1545
122.6 IPS |
|
|
Object Detection (HP)
|
98% |
2537
201.9 IPS |
|
|
Object Detection (Q)
|
90% |
4736
378.6 IPS |
|
|
Face Detection (SP)
|
100% |
5283
62.8 IPS |
|
|
Face Detection (HP)
|
100% |
8180
97.2 IPS |
|
|
Face Detection (Q)
|
100% |
10786
128.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5276
40.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
8906
68.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
12228
95.1 IPS |
|
|
Style Transfer (SP)
|
100% |
11684
15.0 IPS |
|
|
Style Transfer (HP)
|
100% |
18544
23.8 IPS |
|
|
Style Transfer (Q)
|
98% |
31117
40.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2128
78.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3485
128.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7223
267.5 IPS |
|
|
Text Classification (SP)
|
71% |
1293
1.87 KIPS |
|
|
Text Classification (HP)
|
71% |
1590
2.30 KIPS |
|
|
Text Classification (Q)
|
92% |
1614
2.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
1210
20.8 IPS |
|
|
Machine Translation (HP)
|
98% |
1977
34.2 IPS |
|
|
Machine Translation (Q)
|
100% |
1999
34.4 IPS |
