Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
38451
Single Precision Score
63768
Half Precision Score
28996
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 19 2025 12:59 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 |
| 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, 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 | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15447
2.87 KIPS |
|
|
Image Classification (HP)
|
100% |
23035
4.28 KIPS |
|
|
Image Classification (Q)
|
100% |
13541
2.52 KIPS |
|
|
Image Segmentation (SP)
|
100% |
27955
453.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
39060
633.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
24883
404.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
247236
288.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
738314
861.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
211619
247.9 IPS |
|
|
Object Detection (SP)
|
100% |
19201
1.52 KIPS |
|
|
Object Detection (HP)
|
100% |
28069
2.23 KIPS |
|
|
Object Detection (Q)
|
86% |
16369
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
53992
641.5 IPS |
|
|
Face Detection (HP)
|
100% |
76708
911.5 IPS |
|
|
Face Detection (Q)
|
97% |
44461
530.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
94868
730.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
180717
1.39 KIPS |
|
|
Depth Estimation (Q)
|
78% |
69316
553.5 IPS |
|
|
Style Transfer (SP)
|
100% |
365051
469.3 IPS |
|
|
Style Transfer (HP)
|
100% |
1171146
1.51 KIPS |
|
|
Style Transfer (Q)
|
98% |
317069
408.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
59725
2.21 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
92765
3.43 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
44606
1.65 KIPS |
|
|
Text Classification (SP)
|
100% |
4328
5.78 KIPS |
|
|
Text Classification (HP)
|
100% |
5562
7.42 KIPS |
|
|
Text Classification (Q)
|
97% |
2624
3.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
7131
122.8 IPS |
|
|
Machine Translation (HP)
|
100% |
7119
122.6 IPS |
|
|
Machine Translation (Q)
|
70% |
3148
59.0 IPS |
