Micro-Star International Co., Ltd. Vector 17 HX AI A2XWIG
Geekbench AI Score
28273
Single Precision Score
48786
Half Precision Score
21860
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | TomKauw |
| Upload Date | August 14 2025 01:55 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector 17 HX AI A2XWIG |
| Motherboard | Micro-Star International Co., Ltd. MS-17S3 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11331
2.11 KIPS |
|
|
Image Classification (HP)
|
100% |
18786
3.49 KIPS |
|
|
Image Classification (Q)
|
100% |
10175
1.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21529
349.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
31486
510.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
19299
313.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
160644
187.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
449092
524.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
143573
168.2 IPS |
|
|
Object Detection (SP)
|
100% |
14026
1.11 KIPS |
|
|
Object Detection (HP)
|
100% |
23081
1.83 KIPS |
|
|
Object Detection (Q)
|
86% |
11749
944.0 IPS |
|
|
Face Detection (SP)
|
100% |
41556
493.8 IPS |
|
|
Face Detection (HP)
|
100% |
60004
713.0 IPS |
|
|
Face Detection (Q)
|
97% |
35124
418.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
68569
528.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
130250
1.00 KIPS |
|
|
Depth Estimation (Q)
|
78% |
53757
429.4 IPS |
|
|
Style Transfer (SP)
|
100% |
255381
328.3 IPS |
|
|
Style Transfer (HP)
|
100% |
833957
1.07 KIPS |
|
|
Style Transfer (Q)
|
98% |
217557
280.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39988
1.48 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69374
2.56 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31547
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3409
4.55 KIPS |
|
|
Text Classification (HP)
|
100% |
4476
5.97 KIPS |
|
|
Text Classification (Q)
|
97% |
2071
2.77 KIPS |
|
|
Machine Translation (SP)
|
100% |
5987
103.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6156
106.0 IPS |
|
|
Machine Translation (Q)
|
70% |
2804
52.6 IPS |
