GETAC S510
Geekbench AI Score
1528
Single Precision Score
440
Half Precision Score
2734
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | jefflin66 |
| Upload Date | December 24 2024 07:41 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core 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% |
1229
228.5 IPS |
|
|
Image Classification (HP)
|
100% |
112
20.8 IPS |
|
|
Image Classification (Q)
|
99% |
2210
412.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
797
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
155
2.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
1817
29.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2156
2.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
1447
1.69 IPS |
|
|
Pose Estimation (Q)
|
95% |
10559
12.4 IPS |
|
|
Object Detection (SP)
|
100% |
1246
98.8 IPS |
|
|
Object Detection (HP)
|
100% |
129
10.3 IPS |
|
|
Object Detection (Q)
|
88% |
1180
94.6 IPS |
|
|
Face Detection (SP)
|
100% |
1616
19.2 IPS |
|
|
Face Detection (HP)
|
100% |
181
2.15 IPS |
|
|
Face Detection (Q)
|
97% |
2638
31.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
3420
26.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
508
3.92 IPS |
|
|
Depth Estimation (Q)
|
76% |
5393
43.5 IPS |
|
|
Style Transfer (SP)
|
100% |
4945
6.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4068
5.23 IPS |
|
|
Style Transfer (Q)
|
98% |
12008
15.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
986
36.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
969
35.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2122
78.6 IPS |
|
|
Text Classification (SP)
|
100% |
1143
1.53 KIPS |
|
|
Text Classification (HP)
|
100% |
476
636.0 IPS |
|
|
Text Classification (Q)
|
97% |
1033
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
860
14.8 IPS |
|
|
Machine Translation (HP)
|
100% |
492
8.48 IPS |
|
|
Machine Translation (Q)
|
60% |
1247
27.8 IPS |
