Micro-Star International Co., Ltd. MS-7E32
Geekbench AI Score
29078
Single Precision Score
51138
Half Precision Score
22498
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | wargames06 |
| Upload Date | April 11 2025 03:04 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E32 |
| Motherboard | Micro-Star International Co., Ltd. MAG Z890 TOMAHAWK WIFI (MS-7E32) |
| 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% |
11375
2.12 KIPS |
|
|
Image Classification (HP)
|
100% |
19614
3.65 KIPS |
|
|
Image Classification (Q)
|
100% |
10128
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
22586
366.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
34627
561.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
20519
333.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
167945
196.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
473155
552.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
139522
163.4 IPS |
|
|
Object Detection (SP)
|
100% |
15370
1.22 KIPS |
|
|
Object Detection (HP)
|
100% |
25577
2.03 KIPS |
|
|
Object Detection (Q)
|
83% |
12975
1.05 KIPS |
|
|
Face Detection (SP)
|
100% |
42030
499.4 IPS |
|
|
Face Detection (HP)
|
100% |
62113
738.0 IPS |
|
|
Face Detection (Q)
|
97% |
35575
424.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
69193
533.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
126021
970.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
55487
442.9 IPS |
|
|
Style Transfer (SP)
|
100% |
231020
297.0 IPS |
|
|
Style Transfer (HP)
|
100% |
796946
1.02 KIPS |
|
|
Style Transfer (Q)
|
98% |
202071
260.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40788
1.51 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
75417
2.78 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
32794
1.21 KIPS |
|
|
Text Classification (SP)
|
100% |
3706
4.95 KIPS |
|
|
Text Classification (HP)
|
100% |
4693
6.26 KIPS |
|
|
Text Classification (Q)
|
97% |
2309
3.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
6418
110.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6740
116.1 IPS |
|
|
Machine Translation (Q)
|
70% |
2925
54.9 IPS |
