| User | SkatterBencher |
| Upload Date | April 24 2025 07:59 AM |
| Views | 10 |
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG MAXIMUS Z890 APEX |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) 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 | 48.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5708
1.06 KIPS |
|
|
Image Classification (HP)
|
100% |
8530
1.59 KIPS |
|
|
Image Classification (Q)
|
100% |
11250
2.09 KIPS |
|
|
Image Segmentation (SP)
|
100% |
5605
90.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12762
206.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
17989
291.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
17624
20.6 IPS |
|
|
Pose Estimation (HP)
|
99% |
16447
19.2 IPS |
|
|
Pose Estimation (Q)
|
97% |
53378
62.5 IPS |
|
|
Object Detection (SP)
|
100% |
5247
416.2 IPS |
|
|
Object Detection (HP)
|
100% |
8198
650.2 IPS |
|
|
Object Detection (Q)
|
88% |
13344
1.07 KIPS |
|
|
Face Detection (SP)
|
100% |
10890
129.4 IPS |
|
|
Face Detection (HP)
|
100% |
21210
252.0 IPS |
|
|
Face Detection (Q)
|
100% |
32840
390.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
18308
141.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
31706
245.1 IPS |
|
|
Depth Estimation (Q)
|
89% |
36677
285.1 IPS |
|
|
Style Transfer (SP)
|
100% |
43381
55.8 IPS |
|
|
Style Transfer (HP)
|
100% |
58627
75.4 IPS |
|
|
Style Transfer (Q)
|
98% |
122520
158.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7634
281.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13694
505.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
21453
794.5 IPS |
|
|
Text Classification (SP)
|
71% |
2269
3.28 KIPS |
|
|
Text Classification (HP)
|
71% |
3478
5.03 KIPS |
|
|
Text Classification (Q)
|
92% |
3615
4.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
3115
53.7 IPS |
|
|
Machine Translation (HP)
|
96% |
4381
75.8 IPS |
|
|
Machine Translation (Q)
|
100% |
4383
75.5 IPS |