Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
38361
Single Precision Score
64002
Half Precision Score
28878
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 06:33 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 i7-14700K |
| Topology | 1 Processor, 20 Cores, 28 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15415
2.87 KIPS |
|
|
Image Classification (HP)
|
100% |
22887
4.26 KIPS |
|
|
Image Classification (Q)
|
100% |
13474
2.51 KIPS |
|
|
Image Segmentation (SP)
|
100% |
27913
452.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
39379
638.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
24927
405.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
245646
286.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
730679
852.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
211009
247.2 IPS |
|
|
Object Detection (SP)
|
100% |
19189
1.52 KIPS |
|
|
Object Detection (HP)
|
100% |
28596
2.27 KIPS |
|
|
Object Detection (Q)
|
86% |
16350
1.31 KIPS |
|
|
Face Detection (SP)
|
100% |
53593
636.8 IPS |
|
|
Face Detection (HP)
|
100% |
77204
917.4 IPS |
|
|
Face Detection (Q)
|
97% |
44472
530.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
94019
724.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
181172
1.40 KIPS |
|
|
Depth Estimation (Q)
|
78% |
68254
545.0 IPS |
|
|
Style Transfer (SP)
|
100% |
360494
463.4 IPS |
|
|
Style Transfer (HP)
|
100% |
1179743
1.52 KIPS |
|
|
Style Transfer (Q)
|
98% |
313182
403.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
59791
2.21 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
93053
3.44 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
44689
1.65 KIPS |
|
|
Text Classification (SP)
|
100% |
4373
5.84 KIPS |
|
|
Text Classification (HP)
|
100% |
5615
7.49 KIPS |
|
|
Text Classification (Q)
|
97% |
2624
3.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
7164
123.4 IPS |
|
|
Machine Translation (HP)
|
100% |
7104
122.4 IPS |
|
|
Machine Translation (Q)
|
70% |
3123
58.6 IPS |
