Micro-Star International Co., Ltd. Vector 17 HX AI A2XWIG
Geekbench AI Score
8715
Single Precision Score
9043
Half Precision Score
16450
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | TomKauw |
| Upload Date | August 14 2025 01:58 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 275HX |
| 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% |
5644
1.05 KIPS |
|
|
Image Classification (HP)
|
100% |
6375
1.19 KIPS |
|
|
Image Classification (Q)
|
100% |
9967
1.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
8053
130.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
4401
71.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
12681
205.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
13337
15.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
13335
15.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
30573
35.8 IPS |
|
|
Object Detection (SP)
|
100% |
5725
454.1 IPS |
|
|
Object Detection (HP)
|
100% |
6565
520.8 IPS |
|
|
Object Detection (Q)
|
88% |
11136
892.7 IPS |
|
|
Face Detection (SP)
|
100% |
16242
193.0 IPS |
|
|
Face Detection (HP)
|
100% |
19345
229.9 IPS |
|
|
Face Detection (Q)
|
100% |
29357
348.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
14136
108.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
16912
130.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
30694
238.7 IPS |
|
|
Style Transfer (SP)
|
100% |
26933
34.6 IPS |
|
|
Style Transfer (HP)
|
100% |
23354
30.0 IPS |
|
|
Style Transfer (Q)
|
98% |
89543
115.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8087
298.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8382
309.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
17260
639.2 IPS |
|
|
Text Classification (SP)
|
100% |
4087
5.46 KIPS |
|
|
Text Classification (HP)
|
100% |
3239
4.32 KIPS |
|
|
Text Classification (Q)
|
92% |
6067
8.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
3564
61.4 IPS |
|
|
Machine Translation (HP)
|
100% |
7184
123.8 IPS |
|
|
Machine Translation (Q)
|
100% |
3992
68.8 IPS |
