samsung SM-A166W
Geekbench AI Score
315
Single Precision Score
548
Half Precision Score
460
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 27 2026 12:42 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% |
215
39.9 IPS |
|
|
Image Classification (HP)
|
100% |
380
70.7 IPS |
|
|
Image Classification (Q)
|
97% |
315
58.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
563
9.12 IPS |
|
|
Image Segmentation (Q)
|
98% |
543
8.83 IPS |
|
|
Pose Estimation (SP)
|
100% |
1129
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2164
2.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
2089
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
325
25.7 IPS |
|
|
Object Detection (Q)
|
83% |
334
27.0 IPS |
|
|
Face Detection (SP)
|
100% |
595
7.07 IPS |
|
|
Face Detection (HP)
|
100% |
1170
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1049
12.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.90 IPS |
|
|
Depth Estimation (HP)
|
98% |
1487
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1160
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1832
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4040
5.19 IPS |
|
|
Style Transfer (Q)
|
98% |
3992
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
419
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
765
28.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
757
28.0 IPS |
|
|
Text Classification (SP)
|
35% |
9
85.4 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.6 IPS |
|
|
Text Classification (Q)
|
32% |
12
154.3 IPS |
|
|
Machine Translation (SP)
|
100% |
268
4.62 IPS |
|
|
Machine Translation (HP)
|
100% |
338
5.83 IPS |
|
|
Machine Translation (Q)
|
43% |
82
4.78 IPS |
