| User | SkatterBencher |
| Upload Date | April 27 2025 04:13 AM |
| Views | 13 |
| 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% |
6131
1.14 KIPS |
|
|
Image Classification (HP)
|
100% |
9260
1.72 KIPS |
|
|
Image Classification (Q)
|
100% |
12072
2.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
6154
99.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
13841
224.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
19907
322.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
18618
21.7 IPS |
|
|
Pose Estimation (HP)
|
99% |
17350
20.3 IPS |
|
|
Pose Estimation (Q)
|
97% |
56421
66.1 IPS |
|
|
Object Detection (SP)
|
100% |
5653
448.4 IPS |
|
|
Object Detection (HP)
|
100% |
8885
704.7 IPS |
|
|
Object Detection (Q)
|
88% |
14494
1.16 KIPS |
|
|
Face Detection (SP)
|
100% |
12200
145.0 IPS |
|
|
Face Detection (HP)
|
100% |
23229
276.0 IPS |
|
|
Face Detection (Q)
|
100% |
35218
418.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
19565
150.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
34329
265.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
39407
306.3 IPS |
|
|
Style Transfer (SP)
|
100% |
46054
59.2 IPS |
|
|
Style Transfer (HP)
|
100% |
62595
80.5 IPS |
|
|
Style Transfer (Q)
|
98% |
129971
167.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8135
300.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14588
538.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22914
848.6 IPS |
|
|
Text Classification (SP)
|
71% |
2474
3.58 KIPS |
|
|
Text Classification (HP)
|
71% |
3807
5.51 KIPS |
|
|
Text Classification (Q)
|
92% |
3965
5.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
3375
58.1 IPS |
|
|
Machine Translation (HP)
|
96% |
4757
82.2 IPS |
|
|
Machine Translation (Q)
|
100% |
4747
81.8 IPS |