Micro-Star International Co., Ltd. MS-7E17
Geekbench AI Score
44740
Single Precision Score
66623
Half Precision Score
33129
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | September 09 2025 12:53 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 D V2 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E17 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z890 CARBON WIFI (MS-7E17) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285 |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16123
3.00 KIPS |
|
|
Image Classification (HP)
|
100% |
21422
3.98 KIPS |
|
|
Image Classification (Q)
|
100% |
14039
2.61 KIPS |
|
|
Image Segmentation (SP)
|
100% |
32856
532.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
40752
660.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
29901
486.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
385889
450.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
940354
1.10 KIPS |
|
|
Pose Estimation (Q)
|
96% |
314805
368.7 IPS |
|
|
Object Detection (SP)
|
100% |
21934
1.74 KIPS |
|
|
Object Detection (HP)
|
100% |
27655
2.19 KIPS |
|
|
Object Detection (Q)
|
85% |
18297
1.47 KIPS |
|
|
Face Detection (SP)
|
100% |
66820
794.0 IPS |
|
|
Face Detection (HP)
|
100% |
86561
1.03 KIPS |
|
|
Face Detection (Q)
|
97% |
53575
638.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
100426
773.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
184309
1.42 KIPS |
|
|
Depth Estimation (Q)
|
77% |
73266
586.8 IPS |
|
|
Style Transfer (SP)
|
100% |
569918
732.6 IPS |
|
|
Style Transfer (HP)
|
100% |
1573324
2.02 KIPS |
|
|
Style Transfer (Q)
|
98% |
483025
622.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
66962
2.47 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
88579
3.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49441
1.83 KIPS |
|
|
Text Classification (SP)
|
100% |
4194
5.60 KIPS |
|
|
Text Classification (HP)
|
100% |
5150
6.87 KIPS |
|
|
Text Classification (Q)
|
97% |
2350
3.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
6673
114.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6628
114.2 IPS |
|
|
Machine Translation (Q)
|
70% |
2990
56.1 IPS |
