| Upload Date | August 11 2024 08:40 PM |
| Views | 14 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4060 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | System manufacturer System Product Name |
| Motherboard | ASUSTeK Computer INC. Maximus IV GENE-Z |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-2600K |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 42 Stepping 7 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4252
790.7 IPS |
|
|
Image Classification (HP)
|
99% |
7106
1.33 KIPS |
|
|
Image Classification (Q)
|
100% |
3949
734.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
5156
83.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
5673
92.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4929
80.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
77188
90.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
185761
216.8 IPS |
|
|
Pose Estimation (Q)
|
97% |
69515
81.4 IPS |
|
|
Object Detection (SP)
|
100% |
5431
430.8 IPS |
|
|
Object Detection (HP)
|
100% |
7285
577.8 IPS |
|
|
Object Detection (Q)
|
90% |
4997
399.6 IPS |
|
|
Face Detection (SP)
|
100% |
11113
132.0 IPS |
|
|
Face Detection (HP)
|
100% |
14223
169.0 IPS |
|
|
Face Detection (Q)
|
97% |
9874
117.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
29965
230.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
54845
422.5 IPS |
|
|
Depth Estimation (Q)
|
75% |
24075
195.0 IPS |
|
|
Style Transfer (SP)
|
100% |
118149
151.9 IPS |
|
|
Style Transfer (HP)
|
100% |
269712
346.7 IPS |
|
|
Style Transfer (Q)
|
98% |
113118
145.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
21716
801.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
30286
1.12 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
17007
629.8 IPS |
|
|
Text Classification (SP)
|
100% |
2200
2.94 KIPS |
|
|
Text Classification (HP)
|
99% |
2345
3.13 KIPS |
|
|
Text Classification (Q)
|
97% |
1509
2.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
1578
27.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1626
28.0 IPS |
|
|
Machine Translation (Q)
|
60% |
911
20.3 IPS |