Micro-Star International Co., Ltd. MS-7E34
Geekbench AI Score
33152
Single Precision Score
47500
Half Precision Score
25751
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | borders22-rumba |
| Upload Date | June 21 2025 05:02 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E34 |
| Motherboard | Micro-Star International Co., Ltd. PRO Z890-P WIFI (MS-7E34) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265K |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12249
2.28 KIPS |
|
|
Image Classification (HP)
|
99% |
17045
3.18 KIPS |
|
|
Image Classification (Q)
|
100% |
10541
1.96 KIPS |
|
|
Image Segmentation (SP)
|
100% |
23464
380.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
30263
490.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
21149
343.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
258548
301.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
494998
577.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
226486
265.4 IPS |
|
|
Object Detection (SP)
|
100% |
15330
1.22 KIPS |
|
|
Object Detection (HP)
|
100% |
20593
1.63 KIPS |
|
|
Object Detection (Q)
|
85% |
13148
1.06 KIPS |
|
|
Face Detection (SP)
|
100% |
47973
570.0 IPS |
|
|
Face Detection (HP)
|
100% |
62226
739.4 IPS |
|
|
Face Detection (Q)
|
97% |
41177
491.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
79468
612.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
142746
1.10 KIPS |
|
|
Depth Estimation (Q)
|
78% |
61545
491.5 IPS |
|
|
Style Transfer (SP)
|
100% |
376113
483.5 IPS |
|
|
Style Transfer (HP)
|
100% |
808997
1.04 KIPS |
|
|
Style Transfer (Q)
|
98% |
334018
430.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49580
1.83 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
64809
2.39 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
39032
1.45 KIPS |
|
|
Text Classification (SP)
|
100% |
3407
4.55 KIPS |
|
|
Text Classification (HP)
|
99% |
4216
5.63 KIPS |
|
|
Text Classification (Q)
|
97% |
2103
2.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
5812
100.1 IPS |
|
|
Machine Translation (HP)
|
100% |
5664
97.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2780
52.2 IPS |
