Micro-Star International Co., Ltd. MS-7E06
Geekbench AI Score
31652
Single Precision Score
46185
Half Precision Score
24821
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | CelteX86 |
| Upload Date | February 27 2025 09:31 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Professionnel (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E06 |
| Motherboard | Micro-Star International Co., Ltd. PRO Z790-P WIFI (MS-7E06) |
| Power Plan | Performances leves |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900K |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 160.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12700
2.36 KIPS |
|
|
Image Classification (HP)
|
99% |
17983
3.35 KIPS |
|
|
Image Classification (Q)
|
100% |
11083
2.06 KIPS |
|
|
Image Segmentation (SP)
|
100% |
17232
279.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
20589
333.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
16039
260.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
257305
300.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
490969
572.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
226355
265.2 IPS |
|
|
Object Detection (SP)
|
100% |
15385
1.22 KIPS |
|
|
Object Detection (HP)
|
100% |
21701
1.72 KIPS |
|
|
Object Detection (Q)
|
85% |
13394
1.08 KIPS |
|
|
Face Detection (SP)
|
100% |
39987
475.1 IPS |
|
|
Face Detection (HP)
|
100% |
50201
596.5 IPS |
|
|
Face Detection (Q)
|
97% |
35317
421.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
78954
608.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
154605
1.19 KIPS |
|
|
Depth Estimation (Q)
|
78% |
60001
479.2 IPS |
|
|
Style Transfer (SP)
|
100% |
392256
504.3 IPS |
|
|
Style Transfer (HP)
|
100% |
881132
1.13 KIPS |
|
|
Style Transfer (Q)
|
98% |
345848
446.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55110
2.03 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
74296
2.74 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
41618
1.54 KIPS |
|
|
Text Classification (SP)
|
100% |
3908
5.22 KIPS |
|
|
Text Classification (HP)
|
99% |
5080
6.78 KIPS |
|
|
Text Classification (Q)
|
97% |
2322
3.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
4368
75.2 IPS |
|
|
Machine Translation (HP)
|
100% |
4337
74.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2326
43.6 IPS |
