samsung SM-A166W
Geekbench AI Score
306
Single Precision Score
539
Half Precision Score
456
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | aqus |
| Upload Date | January 23 2026 12:03 PM |
| Views | 5 |
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% |
169
31.5 IPS |
|
|
Image Classification (HP)
|
100% |
335
62.3 IPS |
|
|
Image Classification (Q)
|
97% |
300
56.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
564
9.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1130
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2126
2.48 IPS |
|
|
Pose Estimation (Q)
|
95% |
2092
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
332
26.3 IPS |
|
|
Object Detection (Q)
|
83% |
305
24.7 IPS |
|
|
Face Detection (SP)
|
100% |
605
7.19 IPS |
|
|
Face Detection (HP)
|
100% |
1168
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1038
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
771
5.94 IPS |
|
|
Depth Estimation (HP)
|
98% |
1487
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1162
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1829
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
4016
5.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3991
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
412
15.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
749
27.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
745
27.6 IPS |
|
|
Text Classification (SP)
|
35% |
9
85.2 IPS |
|
|
Text Classification (HP)
|
29% |
9
163.7 IPS |
|
|
Text Classification (Q)
|
32% |
13
161.4 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.47 IPS |
|
|
Machine Translation (HP)
|
100% |
332
5.72 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.84 IPS |
