GETAC S510
Geekbench AI Score
1757
Single Precision Score
1796
Half Precision Score
5015
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | jefflin66 |
| Upload Date | August 27 2024 12:48 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 (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% |
1085
201.8 IPS |
|
|
Image Classification (HP)
|
100% |
940
174.8 IPS |
|
|
Image Classification (Q)
|
100% |
3164
588.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1367
22.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1490
24.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
3395
55.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2329
2.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
2459
2.87 IPS |
|
|
Pose Estimation (Q)
|
96% |
8473
9.92 IPS |
|
|
Object Detection (SP)
|
100% |
1003
79.6 IPS |
|
|
Object Detection (HP)
|
100% |
1142
90.6 IPS |
|
|
Object Detection (Q)
|
88% |
2488
199.4 IPS |
|
|
Face Detection (SP)
|
100% |
3218
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
2994
35.6 IPS |
|
|
Face Detection (Q)
|
100% |
6885
81.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2728
21.0 IPS |
|
|
Depth Estimation (HP)
|
100% |
2685
20.7 IPS |
|
|
Depth Estimation (Q)
|
80% |
6761
53.6 IPS |
|
|
Style Transfer (SP)
|
100% |
6666
8.57 IPS |
|
|
Style Transfer (HP)
|
100% |
7148
9.19 IPS |
|
|
Style Transfer (Q)
|
98% |
25510
32.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1326
49.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1591
58.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5338
197.7 IPS |
|
|
Text Classification (SP)
|
100% |
581
774.8 IPS |
|
|
Text Classification (HP)
|
100% |
574
765.5 IPS |
|
|
Text Classification (Q)
|
92% |
2488
3.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
1796
30.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1694
29.2 IPS |
|
|
Machine Translation (Q)
|
85% |
2823
49.4 IPS |
