samsung SM-A166W
Geekbench AI Score
314
Single Precision Score
543
Half Precision Score
452
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 28 2026 12:03 PM |
| Views | 4 |
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% |
171
31.8 IPS |
|
|
Image Classification (HP)
|
100% |
378
70.3 IPS |
|
|
Image Classification (Q)
|
97% |
311
58.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
535
8.66 IPS |
|
|
Image Segmentation (Q)
|
98% |
530
8.62 IPS |
|
|
Pose Estimation (SP)
|
100% |
1132
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2114
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2088
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
177
14.0 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
302
24.4 IPS |
|
|
Face Detection (SP)
|
100% |
623
7.40 IPS |
|
|
Face Detection (HP)
|
100% |
1244
14.8 IPS |
|
|
Face Detection (Q)
|
96% |
1018
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
776
5.98 IPS |
|
|
Depth Estimation (HP)
|
98% |
1481
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1147
10.9 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4006
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3983
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
431
15.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
755
27.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
743
27.5 IPS |
|
|
Text Classification (SP)
|
35% |
10
89.8 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.1 IPS |
|
|
Text Classification (Q)
|
32% |
12
153.8 IPS |
|
|
Machine Translation (SP)
|
100% |
264
4.55 IPS |
|
|
Machine Translation (HP)
|
100% |
332
5.72 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.83 IPS |
