| User | gbench |
| Upload Date | December 20 2024 01:58 AM |
| Views | 13 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285K |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E33 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z890I EDGE TI WIFI (MS-7E33) |
| Power Plan | Ausbalanciert |
| 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 | 96.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5146
956.9 IPS |
|
|
Image Classification (HP)
|
100% |
640
118.9 IPS |
|
|
Image Classification (Q)
|
99% |
8869
1.65 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3156
51.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1256
20.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4629
75.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
16407
19.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
8390
9.79 IPS |
|
|
Pose Estimation (Q)
|
94% |
48745
57.2 IPS |
|
|
Object Detection (SP)
|
100% |
5079
402.9 IPS |
|
|
Object Detection (HP)
|
100% |
891
70.7 IPS |
|
|
Object Detection (Q)
|
86% |
10352
832.0 IPS |
|
|
Face Detection (SP)
|
100% |
14066
167.1 IPS |
|
|
Face Detection (HP)
|
100% |
2151
25.6 IPS |
|
|
Face Detection (Q)
|
97% |
14287
170.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
16697
128.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2978
22.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
24681
196.9 IPS |
|
|
Style Transfer (SP)
|
100% |
34099
43.8 IPS |
|
|
Style Transfer (HP)
|
100% |
19977
25.7 IPS |
|
|
Style Transfer (Q)
|
98% |
34685
44.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5072
187.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3037
112.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4955
183.5 IPS |
|
|
Text Classification (SP)
|
100% |
1618
2.16 KIPS |
|
|
Text Classification (HP)
|
100% |
827
1.10 KIPS |
|
|
Text Classification (Q)
|
97% |
1727
2.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
2442
42.1 IPS |
|
|
Machine Translation (HP)
|
100% |
904
15.6 IPS |
|
|
Machine Translation (Q)
|
65% |
3585
72.0 IPS |