GETAC S510
Geekbench AI Score
2163
Single Precision Score
2164
Half Precision Score
5606
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 26 2024 01:07 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) CoreTM Ultra 7 165U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GETAC S510 |
| Motherboard | GETAC S510 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) CoreTM 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% |
1288
239.6 IPS |
|
|
Image Classification (HP)
|
100% |
1313
244.3 IPS |
|
|
Image Classification (Q)
|
100% |
3733
694.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1715
27.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1951
31.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3889
63.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2693
3.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
2063
2.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
9453
11.1 IPS |
|
|
Object Detection (SP)
|
100% |
1235
97.9 IPS |
|
|
Object Detection (HP)
|
100% |
1280
101.5 IPS |
|
|
Object Detection (Q)
|
88% |
3859
309.3 IPS |
|
|
Face Detection (SP)
|
100% |
3785
45.0 IPS |
|
|
Face Detection (HP)
|
100% |
3746
44.5 IPS |
|
|
Face Detection (Q)
|
100% |
8053
95.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3090
23.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3236
24.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
7901
61.4 IPS |
|
|
Style Transfer (SP)
|
100% |
7102
9.13 IPS |
|
|
Style Transfer (HP)
|
100% |
7479
9.61 IPS |
|
|
Style Transfer (Q)
|
98% |
30436
39.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1565
57.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1506
55.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6090
225.5 IPS |
|
|
Text Classification (SP)
|
100% |
1304
1.74 KIPS |
|
|
Text Classification (HP)
|
100% |
1434
1.91 KIPS |
|
|
Text Classification (Q)
|
92% |
2901
3.90 KIPS |
|
|
Machine Translation (SP)
|
100% |
1804
31.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1704
29.4 IPS |
|
|
Machine Translation (Q)
|
100% |
1693
29.2 IPS |
