| Upload Date | January 29 2026 06:33 AM |
| Views | 3 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. Pro WS TRX50-SAGE WIFI |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | AMD Ryzen Threadripper 7970X |
| Topology | 1 Processor, 32 Cores, 64 Threads |
| Identifier | AuthenticAMD Family 25 Model 24 Stepping 1 |
| Base Frequency | 4.00 GHz |
| Cluster 1 | 32 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12656
2.35 KIPS |
|
|
Image Classification (HP)
|
99% |
18052
3.37 KIPS |
|
|
Image Classification (Q)
|
100% |
11161
2.08 KIPS |
|
|
Image Segmentation (SP)
|
100% |
24781
401.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
33866
549.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
22947
373.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
257865
300.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
511776
597.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
225217
263.9 IPS |
|
|
Object Detection (SP)
|
100% |
16643
1.32 KIPS |
|
|
Object Detection (HP)
|
100% |
24234
1.92 KIPS |
|
|
Object Detection (Q)
|
85% |
14308
1.15 KIPS |
|
|
Face Detection (SP)
|
100% |
50780
603.4 IPS |
|
|
Face Detection (HP)
|
100% |
68209
810.5 IPS |
|
|
Face Detection (Q)
|
97% |
43109
514.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
76941
592.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
149372
1.15 KIPS |
|
|
Depth Estimation (Q)
|
78% |
58934
470.6 IPS |
|
|
Style Transfer (SP)
|
100% |
387830
498.6 IPS |
|
|
Style Transfer (HP)
|
100% |
888317
1.14 KIPS |
|
|
Style Transfer (Q)
|
98% |
334950
431.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
52504
1.94 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
71932
2.66 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
40345
1.49 KIPS |
|
|
Text Classification (SP)
|
100% |
3471
4.63 KIPS |
|
|
Text Classification (HP)
|
99% |
4198
5.60 KIPS |
|
|
Text Classification (Q)
|
97% |
2145
2.87 KIPS |
|
|
Machine Translation (SP)
|
100% |
6260
107.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6237
107.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2750
51.6 IPS |