samsung SM-A166W
Geekbench AI Score
323
Single Precision Score
556
Half Precision Score
473
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 03 2026 02:59 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A166W |
| Model ID | samsung SM-A166W |
| 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% |
168
31.2 IPS |
|
|
Image Classification (HP)
|
100% |
347
64.5 IPS |
|
|
Image Classification (Q)
|
97% |
304
56.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
572
9.27 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1132
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2117
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2084
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
198
15.7 IPS |
|
|
Object Detection (HP)
|
99% |
388
30.8 IPS |
|
|
Object Detection (Q)
|
83% |
353
28.5 IPS |
|
|
Face Detection (SP)
|
100% |
633
7.52 IPS |
|
|
Face Detection (HP)
|
100% |
1205
14.3 IPS |
|
|
Face Detection (Q)
|
96% |
1020
12.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
782
6.03 IPS |
|
|
Depth Estimation (HP)
|
98% |
1484
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1175
11.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1885
2.42 IPS |
|
|
Style Transfer (HP)
|
100% |
4055
5.21 IPS |
|
|
Style Transfer (Q)
|
98% |
3975
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
460
17.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
768
28.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
740
27.4 IPS |
|
|
Text Classification (SP)
|
35% |
11
98.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
155.1 IPS |
|
|
Text Classification (Q)
|
32% |
13
165.2 IPS |
|
|
Machine Translation (SP)
|
100% |
261
4.49 IPS |
|
|
Machine Translation (HP)
|
100% |
346
5.96 IPS |
|
|
Machine Translation (Q)
|
43% |
105
6.13 IPS |
