samsung SM-S166V
Geekbench AI Score
313
Single Precision Score
549
Half Precision Score
460
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 01 2026 10:03 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S166V |
| Model ID | samsung SM-S166V |
| Motherboard | s5e8535 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.37 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
190
35.3 IPS |
|
|
Image Classification (HP)
|
100% |
406
75.4 IPS |
|
|
Image Classification (Q)
|
97% |
326
60.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
563
9.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
522
8.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
1134
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2114
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2092
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
326
25.8 IPS |
|
|
Object Detection (Q)
|
83% |
304
24.6 IPS |
|
|
Face Detection (SP)
|
100% |
610
7.25 IPS |
|
|
Face Detection (HP)
|
100% |
1172
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1068
12.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
764
5.89 IPS |
|
|
Depth Estimation (HP)
|
98% |
1482
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1164
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1839
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4022
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
4012
5.17 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
410
15.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
771
28.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
741
27.5 IPS |
|
|
Text Classification (SP)
|
35% |
10
89.8 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.7 IPS |
|
|
Text Classification (Q)
|
32% |
13
165.2 IPS |
|
|
Machine Translation (SP)
|
100% |
259
4.47 IPS |
|
|
Machine Translation (HP)
|
100% |
330
5.69 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.83 IPS |
