Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
2758
Single Precision Score
4032
Half Precision Score
6319
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 19 2025 03:14 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 i7-14700K |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1709
317.8 IPS |
|
|
Image Classification (HP)
|
100% |
2807
522.1 IPS |
|
|
Image Classification (Q)
|
99% |
4310
803.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2459
39.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
4065
65.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4867
78.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4373
5.10 IPS |
|
|
Pose Estimation (HP)
|
99% |
3181
3.71 IPS |
|
|
Pose Estimation (Q)
|
97% |
13051
15.3 IPS |
|
|
Object Detection (SP)
|
100% |
1523
120.8 IPS |
|
|
Object Detection (HP)
|
98% |
2501
199.0 IPS |
|
|
Object Detection (Q)
|
90% |
4598
367.6 IPS |
|
|
Face Detection (SP)
|
100% |
5101
60.6 IPS |
|
|
Face Detection (HP)
|
100% |
7962
94.6 IPS |
|
|
Face Detection (Q)
|
100% |
10517
125.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5140
39.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
8712
67.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
11992
93.2 IPS |
|
|
Style Transfer (SP)
|
100% |
11368
14.6 IPS |
|
|
Style Transfer (HP)
|
100% |
18084
23.2 IPS |
|
|
Style Transfer (Q)
|
98% |
30264
39.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2079
76.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3390
125.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7011
259.6 IPS |
|
|
Text Classification (SP)
|
71% |
1262
1.83 KIPS |
|
|
Text Classification (HP)
|
71% |
1546
2.24 KIPS |
|
|
Text Classification (Q)
|
92% |
1572
2.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
1166
20.1 IPS |
|
|
Machine Translation (HP)
|
98% |
1904
32.9 IPS |
|
|
Machine Translation (Q)
|
100% |
1917
33.0 IPS |
