samsung SM-A166W
Geekbench AI Score
522
Single Precision Score
508
Half Precision Score
985
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 02:26 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
235
43.7 IPS |
|
|
Image Classification (HP)
|
100% |
234
43.5 IPS |
|
|
Image Classification (Q)
|
100% |
654
121.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
282
4.56 IPS |
|
|
Image Segmentation (HP)
|
100% |
288
4.66 IPS |
|
|
Image Segmentation (Q)
|
98% |
766
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1189
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1167
1.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
1781
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
230
18.3 IPS |
|
|
Object Detection (HP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (Q)
|
83% |
670
54.1 IPS |
|
|
Face Detection (SP)
|
100% |
765
9.09 IPS |
|
|
Face Detection (HP)
|
100% |
691
8.21 IPS |
|
|
Face Detection (Q)
|
95% |
1586
18.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
947
7.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
921
7.09 IPS |
|
|
Depth Estimation (Q)
|
64% |
1478
13.5 IPS |
|
|
Style Transfer (SP)
|
89% |
1873
2.43 IPS |
|
|
Style Transfer (HP)
|
89% |
1812
2.35 IPS |
|
|
Style Transfer (Q)
|
98% |
3720
4.80 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
531
19.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
488
18.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
912
33.8 IPS |
|
|
Text Classification (SP)
|
100% |
256
341.5 IPS |
|
|
Text Classification (HP)
|
100% |
269
358.9 IPS |
|
|
Text Classification (Q)
|
88% |
562
758.5 IPS |
|
|
Machine Translation (SP)
|
100% |
451
7.76 IPS |
|
|
Machine Translation (HP)
|
100% |
427
7.35 IPS |
|
|
Machine Translation (Q)
|
50% |
323
11.5 IPS |
