| Upload Date | July 21 2025 09:32 PM |
| Views | 10 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 275HX |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GIGABYTE AORUS Elite 16 BWH |
| Motherboard | GIGABYTE AORUS Elite 16 BWH |
| Power Plan | Ausbalanciert |
| 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 |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5065
941.9 IPS |
|
|
Image Classification (HP)
|
100% |
650
120.9 IPS |
|
|
Image Classification (Q)
|
99% |
9044
1.69 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2564
41.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1440
23.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
15558
253.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
13082
15.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
7152
8.34 IPS |
|
|
Pose Estimation (Q)
|
94% |
43150
50.6 IPS |
|
|
Object Detection (SP)
|
100% |
4757
377.4 IPS |
|
|
Object Detection (HP)
|
100% |
1030
81.7 IPS |
|
|
Object Detection (Q)
|
86% |
10504
844.2 IPS |
|
|
Face Detection (SP)
|
100% |
14360
170.6 IPS |
|
|
Face Detection (HP)
|
100% |
2349
27.9 IPS |
|
|
Face Detection (Q)
|
97% |
11797
140.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
14422
111.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3172
24.4 IPS |
|
|
Depth Estimation (Q)
|
78% |
22876
182.5 IPS |
|
|
Style Transfer (SP)
|
100% |
27181
34.9 IPS |
|
|
Style Transfer (HP)
|
100% |
14594
18.8 IPS |
|
|
Style Transfer (Q)
|
98% |
29673
38.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4730
174.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3091
114.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6495
240.5 IPS |
|
|
Text Classification (SP)
|
100% |
1629
2.17 KIPS |
|
|
Text Classification (HP)
|
100% |
876
1.17 KIPS |
|
|
Text Classification (Q)
|
97% |
1414
1.89 KIPS |
|
|
Machine Translation (SP)
|
100% |
2752
47.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1277
22.0 IPS |
|
|
Machine Translation (Q)
|
65% |
3844
77.2 IPS |