GETAC S510
Geekbench AI Score
1822
Single Precision Score
1836
Half Precision Score
5030
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | jefflin66 |
| Upload Date | August 27 2024 07:03 AM |
| Views | 4 |
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% |
1192
221.7 IPS |
|
|
Image Classification (HP)
|
100% |
1209
224.8 IPS |
|
|
Image Classification (Q)
|
100% |
3268
607.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1613
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1587
25.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3229
52.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2486
2.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
2328
2.72 IPS |
|
|
Pose Estimation (Q)
|
96% |
8915
10.4 IPS |
|
|
Object Detection (SP)
|
100% |
1048
83.1 IPS |
|
|
Object Detection (HP)
|
100% |
1091
86.6 IPS |
|
|
Object Detection (Q)
|
88% |
2643
211.9 IPS |
|
|
Face Detection (SP)
|
100% |
3194
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
3301
39.2 IPS |
|
|
Face Detection (Q)
|
100% |
6829
81.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2815
21.7 IPS |
|
|
Depth Estimation (HP)
|
100% |
2777
21.4 IPS |
|
|
Depth Estimation (Q)
|
80% |
7116
56.4 IPS |
|
|
Style Transfer (SP)
|
100% |
7236
9.30 IPS |
|
|
Style Transfer (HP)
|
100% |
6808
8.75 IPS |
|
|
Style Transfer (Q)
|
98% |
23068
29.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1302
48.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1513
55.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4994
184.9 IPS |
|
|
Text Classification (SP)
|
100% |
538
718.1 IPS |
|
|
Text Classification (HP)
|
100% |
540
720.2 IPS |
|
|
Text Classification (Q)
|
92% |
2430
3.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
1775
30.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1757
30.3 IPS |
|
|
Machine Translation (Q)
|
85% |
3070
53.7 IPS |
