Micro-Star International Co., Ltd. MS-CF05
Geekbench AI Score
38557
Single Precision Score
64235
Half Precision Score
29001
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 07:20 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% |
15498
2.88 KIPS |
|
|
Image Classification (HP)
|
100% |
23112
4.30 KIPS |
|
|
Image Classification (Q)
|
100% |
13642
2.54 KIPS |
|
|
Image Segmentation (SP)
|
100% |
27986
453.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
39336
637.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
24966
406.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
246770
287.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
733104
855.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
211070
247.2 IPS |
|
|
Object Detection (SP)
|
100% |
19405
1.54 KIPS |
|
|
Object Detection (HP)
|
100% |
28705
2.28 KIPS |
|
|
Object Detection (Q)
|
86% |
16481
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
54159
643.5 IPS |
|
|
Face Detection (HP)
|
100% |
76689
911.2 IPS |
|
|
Face Detection (Q)
|
97% |
44819
534.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
93919
723.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
181967
1.40 KIPS |
|
|
Depth Estimation (Q)
|
78% |
68515
547.1 IPS |
|
|
Style Transfer (SP)
|
100% |
362359
465.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1180602
1.52 KIPS |
|
|
Style Transfer (Q)
|
98% |
313265
403.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
60222
2.22 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
93262
3.44 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
44873
1.66 KIPS |
|
|
Text Classification (SP)
|
100% |
4384
5.85 KIPS |
|
|
Text Classification (HP)
|
100% |
5660
7.56 KIPS |
|
|
Text Classification (Q)
|
97% |
2635
3.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
7186
123.8 IPS |
|
|
Machine Translation (HP)
|
100% |
7189
123.8 IPS |
|
|
Machine Translation (Q)
|
70% |
3124
58.6 IPS |
