| User | O-EtaIXVII | 
| Upload Date | July 05 2025 07:25 AM | 
| Views | 9 | 
| AI Information | |
|---|---|
| Framework | ONNX | 
| Backend | DirectML | 
| Device | NVIDIA GeForce RTX 5090 | 
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (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% | 
18143
 3.37 KIPS  | 
|
| 
Image Classification (HP)
 | 
100% | 
23671
 4.40 KIPS  | 
|
| 
Image Classification (Q)
 | 
100% | 
15497
 2.88 KIPS  | 
|
| 
Image Segmentation (SP)
 | 
100% | 
38324
 621.3 IPS  | 
|
| 
Image Segmentation (HP)
 | 
100% | 
49185
 797.3 IPS  | 
|
| 
Image Segmentation (Q)
 | 
98% | 
34498
 561.0 IPS  | 
|
| 
Pose Estimation (SP)
 | 
100% | 
407416
 475.4 IPS  | 
|
| 
Pose Estimation (HP)
 | 
100% | 
955728
 1.12 KIPS  | 
|
| 
Pose Estimation (Q)
 | 
96% | 
324596
 380.2 IPS  | 
|
| 
Object Detection (SP)
 | 
100% | 
25213
 2.00 KIPS  | 
|
| 
Object Detection (HP)
 | 
100% | 
33338
 2.64 KIPS  | 
|
| 
Object Detection (Q)
 | 
85% | 
20589
 1.66 KIPS  | 
|
| 
Face Detection (SP)
 | 
100% | 
74501
 885.2 IPS  | 
|
| 
Face Detection (HP)
 | 
100% | 
100049
 1.19 KIPS  | 
|
| 
Face Detection (Q)
 | 
97% | 
58635
 699.2 IPS  | 
|
| 
Depth Estimation (SP)
 | 
100% | 
108673
 837.3 IPS  | 
|
| 
Depth Estimation (HP)
 | 
99% | 
198524
 1.53 KIPS  | 
|
| 
Depth Estimation (Q)
 | 
77% | 
77152
 618.0 IPS  | 
|
| 
Style Transfer (SP)
 | 
100% | 
605751
 778.7 IPS  | 
|
| 
Style Transfer (HP)
 | 
100% | 
1773029
 2.28 KIPS  | 
|
| 
Style Transfer (Q)
 | 
98% | 
508176
 655.3 IPS  | 
|
| 
Image Super-Resolution (SP)
 | 
100% | 
75784
 2.80 KIPS  | 
|
| 
Image Super-Resolution (HP)
 | 
100% | 
101441
 3.75 KIPS  | 
|
| 
Image Super-Resolution (Q)
 | 
99% | 
53861
 1.99 KIPS  | 
|
| 
Text Classification (SP)
 | 
100% | 
4499
 6.01 KIPS  | 
|
| 
Text Classification (HP)
 | 
100% | 
5458
 7.29 KIPS  | 
|
| 
Text Classification (Q)
 | 
97% | 
2588
 3.47 KIPS  | 
|
| 
Machine Translation (SP)
 | 
100% | 
7672
 132.2 IPS  | 
|
| 
Machine Translation (HP)
 | 
100% | 
7679
 132.3 IPS  | 
|
| 
Machine Translation (Q)
 | 
70% | 
3266
 61.3 IPS  |