| User | SkatterBencher |
| Upload Date | May 21 2025 05:37 AM |
| 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 | 32.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7010
1.30 KIPS |
|
|
Image Classification (HP)
|
100% |
10205
1.90 KIPS |
|
|
Image Classification (Q)
|
100% |
13547
2.52 KIPS |
|
|
Image Segmentation (SP)
|
100% |
6421
104.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15449
250.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
22895
371.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
23275
27.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
21139
24.7 IPS |
|
|
Pose Estimation (Q)
|
97% |
70519
82.6 IPS |
|
|
Object Detection (SP)
|
100% |
6463
512.7 IPS |
|
|
Object Detection (HP)
|
100% |
10060
797.9 IPS |
|
|
Object Detection (Q)
|
88% |
15998
1.28 KIPS |
|
|
Face Detection (SP)
|
100% |
12778
151.8 IPS |
|
|
Face Detection (HP)
|
100% |
24439
290.4 IPS |
|
|
Face Detection (Q)
|
100% |
37518
445.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
22913
176.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
39641
306.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
46626
362.4 IPS |
|
|
Style Transfer (SP)
|
100% |
56038
72.0 IPS |
|
|
Style Transfer (HP)
|
100% |
74286
95.5 IPS |
|
|
Style Transfer (Q)
|
98% |
160663
207.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9872
364.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17675
652.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27523
1.02 KIPS |
|
|
Text Classification (SP)
|
71% |
2726
3.94 KIPS |
|
|
Text Classification (HP)
|
71% |
4241
6.14 KIPS |
|
|
Text Classification (Q)
|
92% |
4349
5.84 KIPS |
|
|
Machine Translation (SP)
|
100% |
3728
64.2 IPS |
|
|
Machine Translation (HP)
|
96% |
5208
90.0 IPS |
|
|
Machine Translation (Q)
|
100% |
5183
89.3 IPS |