Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
2751
Single Precision Score
4012
Half Precision Score
6276
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 06:11 AM |
| Views | 4 |
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% |
1708
317.6 IPS |
|
|
Image Classification (HP)
|
100% |
2807
522.0 IPS |
|
|
Image Classification (Q)
|
99% |
4294
801.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2477
40.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
4060
65.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
4866
78.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4376
5.11 IPS |
|
|
Pose Estimation (HP)
|
99% |
3185
3.72 IPS |
|
|
Pose Estimation (Q)
|
97% |
13091
15.3 IPS |
|
|
Object Detection (SP)
|
100% |
1524
120.9 IPS |
|
|
Object Detection (HP)
|
98% |
2494
198.5 IPS |
|
|
Object Detection (Q)
|
90% |
4586
366.6 IPS |
|
|
Face Detection (SP)
|
100% |
5117
60.8 IPS |
|
|
Face Detection (HP)
|
100% |
7902
93.9 IPS |
|
|
Face Detection (Q)
|
100% |
10375
123.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
5106
39.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
8684
67.1 IPS |
|
|
Depth Estimation (Q)
|
89% |
11939
92.8 IPS |
|
|
Style Transfer (SP)
|
100% |
11335
14.6 IPS |
|
|
Style Transfer (HP)
|
100% |
17982
23.1 IPS |
|
|
Style Transfer (Q)
|
98% |
30143
38.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2053
75.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3361
124.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6960
257.7 IPS |
|
|
Text Classification (SP)
|
71% |
1252
1.81 KIPS |
|
|
Text Classification (HP)
|
71% |
1537
2.22 KIPS |
|
|
Text Classification (Q)
|
92% |
1560
2.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
1160
20.0 IPS |
|
|
Machine Translation (HP)
|
98% |
1877
32.4 IPS |
|
|
Machine Translation (Q)
|
100% |
1866
32.1 IPS |
