GETAC S510
Geekbench AI Score
1555
Single Precision Score
1612
Half Precision Score
4850
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | jefflin66 |
| Upload Date | August 26 2024 05:34 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 155U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GETAC S510 |
| Motherboard | GETAC S510 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155U |
| Topology | 1 Processor, 12 Cores, 14 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
918
170.7 IPS |
|
|
Image Classification (HP)
|
100% |
1134
210.9 IPS |
|
|
Image Classification (Q)
|
100% |
3651
679.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1477
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1504
24.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
3071
49.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1715
2.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
1773
2.07 IPS |
|
|
Pose Estimation (Q)
|
96% |
6486
7.60 IPS |
|
|
Object Detection (SP)
|
100% |
985
78.1 IPS |
|
|
Object Detection (HP)
|
100% |
971
77.0 IPS |
|
|
Object Detection (Q)
|
88% |
3087
247.5 IPS |
|
|
Face Detection (SP)
|
100% |
3254
38.7 IPS |
|
|
Face Detection (HP)
|
100% |
3244
38.6 IPS |
|
|
Face Detection (Q)
|
100% |
7823
93.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2369
18.3 IPS |
|
|
Depth Estimation (HP)
|
100% |
2406
18.5 IPS |
|
|
Depth Estimation (Q)
|
80% |
6349
50.3 IPS |
|
|
Style Transfer (SP)
|
100% |
5374
6.91 IPS |
|
|
Style Transfer (HP)
|
100% |
5304
6.82 IPS |
|
|
Style Transfer (Q)
|
98% |
27194
35.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1133
41.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1222
45.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6098
225.8 IPS |
|
|
Text Classification (SP)
|
100% |
603
805.0 IPS |
|
|
Text Classification (HP)
|
100% |
598
798.6 IPS |
|
|
Text Classification (Q)
|
92% |
1931
2.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
1283
22.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1342
23.1 IPS |
|
|
Machine Translation (Q)
|
85% |
2018
35.3 IPS |
