| User | gethen |
| Upload Date | June 18 2025 01:54 AM |
| Views | 12 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 265KF |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Gigabyte Technology Co., Ltd. B860I AORUS PRO ICE |
| Motherboard | Gigabyte Technology Co., Ltd. B860I AORUS PRO ICE |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265KF |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4269
793.8 IPS |
|
|
Image Classification (HP)
|
100% |
737
137.0 IPS |
|
|
Image Classification (Q)
|
99% |
7961
1.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2718
44.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1410
22.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
4212
68.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
13110
15.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
7131
8.32 IPS |
|
|
Pose Estimation (Q)
|
94% |
41178
48.3 IPS |
|
|
Object Detection (SP)
|
100% |
4267
338.4 IPS |
|
|
Object Detection (HP)
|
100% |
1004
79.6 IPS |
|
|
Object Detection (Q)
|
86% |
10225
821.7 IPS |
|
|
Face Detection (SP)
|
100% |
11840
140.7 IPS |
|
|
Face Detection (HP)
|
100% |
2329
27.7 IPS |
|
|
Face Detection (Q)
|
97% |
13022
155.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
14118
108.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3192
24.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
19499
155.6 IPS |
|
|
Style Transfer (SP)
|
100% |
27727
35.6 IPS |
|
|
Style Transfer (HP)
|
100% |
19000
24.4 IPS |
|
|
Style Transfer (Q)
|
98% |
31062
40.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4657
171.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2736
101.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5470
202.6 IPS |
|
|
Text Classification (SP)
|
100% |
1770
2.36 KIPS |
|
|
Text Classification (HP)
|
100% |
856
1.14 KIPS |
|
|
Text Classification (Q)
|
97% |
1714
2.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
2697
46.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1047
18.0 IPS |
|
|
Machine Translation (Q)
|
65% |
4289
86.2 IPS |