| Upload Date | November 10 2025 02:02 AM |
| Views | 3 |
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector 17 HX AI A2XWJG |
| Motherboard | Micro-Star International Co., Ltd. MS-17S3 |
| CPU Information | |
|---|---|
| Name | Intel Core 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 |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5065
941.9 IPS |
|
|
Image Classification (HP)
|
100% |
6875
1.28 KIPS |
|
|
Image Classification (Q)
|
100% |
9523
1.77 KIPS |
|
|
Image Segmentation (SP)
|
100% |
7084
114.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2886
46.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3920
63.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
10879
12.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
34457
40.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
74459
87.2 IPS |
|
|
Object Detection (SP)
|
100% |
4951
392.7 IPS |
|
|
Object Detection (HP)
|
100% |
6155
488.2 IPS |
|
|
Object Detection (Q)
|
87% |
9987
801.5 IPS |
|
|
Face Detection (SP)
|
100% |
14897
177.0 IPS |
|
|
Face Detection (HP)
|
100% |
16878
200.5 IPS |
|
|
Face Detection (Q)
|
100% |
32085
381.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
12530
96.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
18338
141.3 IPS |
|
|
Depth Estimation (Q)
|
88% |
34403
267.7 IPS |
|
|
Style Transfer (SP)
|
100% |
30350
39.0 IPS |
|
|
Style Transfer (HP)
|
100% |
51923
66.7 IPS |
|
|
Style Transfer (Q)
|
98% |
96021
123.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6716
248.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14121
521.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
23276
862.0 IPS |
|
|
Text Classification (SP)
|
100% |
3949
5.27 KIPS |
|
|
Text Classification (HP)
|
100% |
2029
2.71 KIPS |
|
|
Text Classification (Q)
|
92% |
2028
2.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3975
68.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4411
76.0 IPS |
|
|
Machine Translation (Q)
|
100% |
4459
76.8 IPS |