| User | gethen |
| Upload Date | July 01 2025 03:40 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% |
5214
969.7 IPS |
|
|
Image Classification (HP)
|
100% |
806
149.8 IPS |
|
|
Image Classification (Q)
|
99% |
9585
1.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2511
40.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1503
24.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4306
70.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
14184
16.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
7950
9.28 IPS |
|
|
Pose Estimation (Q)
|
94% |
46906
55.0 IPS |
|
|
Object Detection (SP)
|
100% |
4822
382.5 IPS |
|
|
Object Detection (HP)
|
100% |
1096
87.0 IPS |
|
|
Object Detection (Q)
|
86% |
10688
858.9 IPS |
|
|
Face Detection (SP)
|
100% |
13530
160.8 IPS |
|
|
Face Detection (HP)
|
100% |
2104
25.0 IPS |
|
|
Face Detection (Q)
|
97% |
13917
165.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
15735
121.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3477
26.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
24553
195.9 IPS |
|
|
Style Transfer (SP)
|
100% |
29217
37.6 IPS |
|
|
Style Transfer (HP)
|
100% |
20100
25.8 IPS |
|
|
Style Transfer (Q)
|
98% |
28394
36.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3977
146.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3060
113.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4657
172.5 IPS |
|
|
Text Classification (SP)
|
100% |
1912
2.55 KIPS |
|
|
Text Classification (HP)
|
100% |
962
1.28 KIPS |
|
|
Text Classification (Q)
|
97% |
1724
2.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
2867
49.4 IPS |
|
|
Machine Translation (HP)
|
100% |
897
15.5 IPS |
|
|
Machine Translation (Q)
|
65% |
3838
77.1 IPS |