| Upload Date | December 07 2025 05:02 AM |
| Views | 2 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285K |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG STRIX Z890-F GAMING WIFI |
| Power Plan | Hg prestanda |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4975
925.2 IPS |
|
|
Image Classification (HP)
|
100% |
672
125.0 IPS |
|
|
Image Classification (Q)
|
99% |
9595
1.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2991
48.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1334
21.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
16889
274.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
14005
16.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
7557
8.82 IPS |
|
|
Pose Estimation (Q)
|
94% |
44415
52.1 IPS |
|
|
Object Detection (SP)
|
100% |
4646
368.5 IPS |
|
|
Object Detection (HP)
|
100% |
964
76.5 IPS |
|
|
Object Detection (Q)
|
86% |
10592
851.3 IPS |
|
|
Face Detection (SP)
|
100% |
14327
170.2 IPS |
|
|
Face Detection (HP)
|
100% |
2125
25.2 IPS |
|
|
Face Detection (Q)
|
97% |
13575
161.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
15332
118.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3109
24.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
20173
161.0 IPS |
|
|
Style Transfer (SP)
|
100% |
29574
38.0 IPS |
|
|
Style Transfer (HP)
|
100% |
17950
23.1 IPS |
|
|
Style Transfer (Q)
|
98% |
32023
41.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5196
191.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3169
117.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7095
262.7 IPS |
|
|
Text Classification (SP)
|
100% |
1754
2.34 KIPS |
|
|
Text Classification (HP)
|
100% |
1043
1.39 KIPS |
|
|
Text Classification (Q)
|
97% |
1403
1.88 KIPS |
|
|
Machine Translation (SP)
|
100% |
2990
51.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1422
24.5 IPS |
|
|
Machine Translation (Q)
|
65% |
3704
74.4 IPS |