| User | SkatterBencher |
| Upload Date | April 11 2025 02:50 PM |
| Views | 14 |
| 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% |
4031
749.7 IPS |
|
|
Image Classification (HP)
|
100% |
6237
1.16 KIPS |
|
|
Image Classification (Q)
|
100% |
8218
1.53 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3991
64.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
8861
143.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
12813
207.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
12204
14.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
11386
13.3 IPS |
|
|
Pose Estimation (Q)
|
97% |
36947
43.3 IPS |
|
|
Object Detection (SP)
|
100% |
3663
290.6 IPS |
|
|
Object Detection (HP)
|
100% |
5993
475.4 IPS |
|
|
Object Detection (Q)
|
88% |
9791
784.7 IPS |
|
|
Face Detection (SP)
|
100% |
8066
95.8 IPS |
|
|
Face Detection (HP)
|
100% |
15836
188.2 IPS |
|
|
Face Detection (Q)
|
100% |
24591
292.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
12787
98.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
22549
174.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
26173
203.4 IPS |
|
|
Style Transfer (SP)
|
100% |
30283
38.9 IPS |
|
|
Style Transfer (HP)
|
100% |
41187
52.9 IPS |
|
|
Style Transfer (Q)
|
98% |
84638
109.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5295
195.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9541
352.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15228
564.0 IPS |
|
|
Text Classification (SP)
|
71% |
1710
2.47 KIPS |
|
|
Text Classification (HP)
|
71% |
2631
3.81 KIPS |
|
|
Text Classification (Q)
|
92% |
2796
3.76 KIPS |
|
|
Machine Translation (SP)
|
100% |
2305
39.7 IPS |
|
|
Machine Translation (HP)
|
96% |
3336
57.7 IPS |
|
|
Machine Translation (Q)
|
100% |
3321
57.2 IPS |