GETAC S510
Geekbench AI Score
1646
Single Precision Score
1724
Half Precision Score
4999
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | jefflin66 |
| Upload Date | August 27 2024 08:30 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 165U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GETAC S510 |
| Motherboard | GETAC S510 |
| Power Plan | Extreme |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 165U |
| 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 | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1232
229.2 IPS |
|
|
Image Classification (HP)
|
100% |
1086
202.0 IPS |
|
|
Image Classification (Q)
|
100% |
3614
672.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1469
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1707
27.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3117
50.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1977
2.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
1928
2.25 IPS |
|
|
Pose Estimation (Q)
|
96% |
6437
7.54 IPS |
|
|
Object Detection (SP)
|
100% |
946
75.0 IPS |
|
|
Object Detection (HP)
|
100% |
968
76.8 IPS |
|
|
Object Detection (Q)
|
88% |
2899
232.4 IPS |
|
|
Face Detection (SP)
|
100% |
2803
33.3 IPS |
|
|
Face Detection (HP)
|
100% |
3197
38.0 IPS |
|
|
Face Detection (Q)
|
100% |
6755
80.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2452
18.9 IPS |
|
|
Depth Estimation (HP)
|
100% |
2840
21.9 IPS |
|
|
Depth Estimation (Q)
|
80% |
7462
59.1 IPS |
|
|
Style Transfer (SP)
|
100% |
6595
8.48 IPS |
|
|
Style Transfer (HP)
|
100% |
6498
8.35 IPS |
|
|
Style Transfer (Q)
|
98% |
26027
33.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1263
46.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1174
43.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5098
188.8 IPS |
|
|
Text Classification (SP)
|
100% |
541
722.3 IPS |
|
|
Text Classification (HP)
|
100% |
590
786.9 IPS |
|
|
Text Classification (Q)
|
92% |
2381
3.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
1394
24.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1645
28.3 IPS |
|
|
Machine Translation (Q)
|
85% |
2917
51.0 IPS |
