Micro-Star International Co., Ltd. MS-7E24
Geekbench AI Score
22208
Single Precision Score
40600
Half Precision Score
17347
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | July 10 2025 10:22 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5060 Ti |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E24 |
| Motherboard | Micro-Star International Co., Ltd. B650M GAMING PLUS WIFI (MS-7E24) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 9600X |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
9606
1.79 KIPS |
|
|
Image Classification (HP)
|
100% |
16865
3.14 KIPS |
|
|
Image Classification (Q)
|
100% |
8779
1.63 KIPS |
|
|
Image Segmentation (SP)
|
100% |
14208
230.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
19898
322.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
13354
217.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
120591
140.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
378872
442.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
113659
133.1 IPS |
|
|
Object Detection (SP)
|
100% |
11635
922.9 IPS |
|
|
Object Detection (HP)
|
100% |
20665
1.64 KIPS |
|
|
Object Detection (Q)
|
83% |
9977
806.1 IPS |
|
|
Face Detection (SP)
|
100% |
28360
337.0 IPS |
|
|
Face Detection (HP)
|
100% |
44468
528.4 IPS |
|
|
Face Detection (Q)
|
97% |
24664
294.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
54423
419.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
112617
867.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
43690
348.7 IPS |
|
|
Style Transfer (SP)
|
100% |
169401
217.8 IPS |
|
|
Style Transfer (HP)
|
100% |
586567
754.0 IPS |
|
|
Style Transfer (Q)
|
98% |
148912
192.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
34482
1.27 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
66724
2.46 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
25666
950.4 IPS |
|
|
Text Classification (SP)
|
100% |
3947
5.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5013
6.69 KIPS |
|
|
Text Classification (Q)
|
97% |
2425
3.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
4284
73.8 IPS |
|
|
Machine Translation (HP)
|
100% |
4715
81.2 IPS |
|
|
Machine Translation (Q)
|
70% |
1859
34.9 IPS |
