| User | pingwinator |
| Upload Date | August 16 2024 01:34 PM |
| Views | 11 |
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | 13th Gen Intel(R) Core(TM) i5-13600 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Gigabyte Technology Co., Ltd. B760M AORUS ELITE AX |
| Motherboard | Gigabyte Technology Co., Ltd. B760M AORUS ELITE AX |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-13600 |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 191 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1676
311.7 IPS |
|
|
Image Classification (HP)
|
100% |
1650
306.8 IPS |
|
|
Image Classification (Q)
|
100% |
3701
688.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1974
32.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1991
32.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
3522
57.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
3367
3.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
3370
3.93 IPS |
|
|
Pose Estimation (Q)
|
96% |
12285
14.4 IPS |
|
|
Object Detection (SP)
|
100% |
1644
130.4 IPS |
|
|
Object Detection (HP)
|
100% |
1638
129.9 IPS |
|
|
Object Detection (Q)
|
88% |
4014
321.7 IPS |
|
|
Face Detection (SP)
|
100% |
5136
61.0 IPS |
|
|
Face Detection (HP)
|
100% |
5114
60.8 IPS |
|
|
Face Detection (Q)
|
100% |
9742
115.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4435
34.2 IPS |
|
|
Depth Estimation (HP)
|
100% |
4405
33.9 IPS |
|
|
Depth Estimation (Q)
|
80% |
10240
81.1 IPS |
|
|
Style Transfer (SP)
|
100% |
10160
13.1 IPS |
|
|
Style Transfer (HP)
|
100% |
10042
12.9 IPS |
|
|
Style Transfer (Q)
|
98% |
21371
27.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2080
76.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2040
75.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6452
239.0 IPS |
|
|
Text Classification (SP)
|
100% |
985
1.32 KIPS |
|
|
Text Classification (HP)
|
100% |
1153
1.54 KIPS |
|
|
Text Classification (Q)
|
92% |
2451
3.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
2418
41.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2374
40.9 IPS |
|
|
Machine Translation (Q)
|
85% |
3147
55.1 IPS |