| User | gethen |
| Upload Date | September 16 2025 02:12 AM |
| Views | 3 |
| 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% |
5058
940.7 IPS |
|
|
Image Classification (HP)
|
100% |
787
146.3 IPS |
|
|
Image Classification (Q)
|
99% |
9487
1.77 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2225
36.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1560
25.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
15652
254.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
13394
15.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
7020
8.19 IPS |
|
|
Pose Estimation (Q)
|
94% |
42088
49.3 IPS |
|
|
Object Detection (SP)
|
100% |
4257
337.7 IPS |
|
|
Object Detection (HP)
|
100% |
1044
82.8 IPS |
|
|
Object Detection (Q)
|
86% |
10806
868.5 IPS |
|
|
Face Detection (SP)
|
100% |
12249
145.5 IPS |
|
|
Face Detection (HP)
|
100% |
2287
27.2 IPS |
|
|
Face Detection (Q)
|
97% |
13107
156.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
14082
108.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3360
25.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
20253
161.6 IPS |
|
|
Style Transfer (SP)
|
100% |
27458
35.3 IPS |
|
|
Style Transfer (HP)
|
100% |
18778
24.1 IPS |
|
|
Style Transfer (Q)
|
98% |
22291
28.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4862
179.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3386
125.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6884
254.9 IPS |
|
|
Text Classification (SP)
|
100% |
1733
2.31 KIPS |
|
|
Text Classification (HP)
|
100% |
921
1.23 KIPS |
|
|
Text Classification (Q)
|
97% |
1539
2.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
2857
49.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1033
17.8 IPS |
|
|
Machine Translation (Q)
|
65% |
3144
63.2 IPS |