GETAC S510
Geekbench AI Score
5341
Single Precision Score
8274
Half Precision Score
12202
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 23 2024 07:35 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| 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% |
3716
691.1 IPS |
|
|
Image Classification (HP)
|
100% |
5330
991.2 IPS |
|
|
Image Classification (Q)
|
100% |
6996
1.30 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3659
59.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
8018
130.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
10861
176.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
11981
14.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
11134
13.0 IPS |
|
|
Pose Estimation (Q)
|
97% |
33091
38.7 IPS |
|
|
Object Detection (SP)
|
100% |
3317
263.1 IPS |
|
|
Object Detection (HP)
|
100% |
5070
402.2 IPS |
|
|
Object Detection (Q)
|
88% |
7932
635.6 IPS |
|
|
Face Detection (SP)
|
100% |
7348
87.3 IPS |
|
|
Face Detection (HP)
|
100% |
14683
174.5 IPS |
|
|
Face Detection (Q)
|
100% |
22783
270.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
12274
94.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
21497
166.1 IPS |
|
|
Depth Estimation (Q)
|
89% |
23867
185.5 IPS |
|
|
Style Transfer (SP)
|
100% |
28920
37.2 IPS |
|
|
Style Transfer (HP)
|
100% |
39838
51.2 IPS |
|
|
Style Transfer (Q)
|
98% |
81662
105.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5169
190.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9186
339.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
14147
523.9 IPS |
|
|
Text Classification (SP)
|
71% |
1426
2.06 KIPS |
|
|
Text Classification (HP)
|
71% |
2174
3.14 KIPS |
|
|
Text Classification (Q)
|
92% |
2384
3.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
1819
31.3 IPS |
|
|
Machine Translation (HP)
|
96% |
2484
43.0 IPS |
|
|
Machine Translation (Q)
|
100% |
2451
42.2 IPS |
