samsung SM-A166W
Geekbench AI Score
516
Single Precision Score
510
Half Precision Score
981
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 03 2026 02:52 PM |
| Views | 9 |
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% |
237
44.1 IPS |
|
|
Image Classification (HP)
|
100% |
237
44.1 IPS |
|
|
Image Classification (Q)
|
100% |
765
142.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
310
5.02 IPS |
|
|
Image Segmentation (HP)
|
100% |
310
5.03 IPS |
|
|
Image Segmentation (Q)
|
98% |
862
14.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1174
1.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1161
1.35 IPS |
|
|
Pose Estimation (Q)
|
84% |
1706
2.02 IPS |
|
|
Object Detection (SP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (HP)
|
100% |
218
17.3 IPS |
|
|
Object Detection (Q)
|
83% |
658
53.2 IPS |
|
|
Face Detection (SP)
|
100% |
688
8.18 IPS |
|
|
Face Detection (HP)
|
100% |
748
8.88 IPS |
|
|
Face Detection (Q)
|
95% |
1587
18.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
959
7.39 IPS |
|
|
Depth Estimation (HP)
|
99% |
891
6.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
1340
12.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1862
2.42 IPS |
|
|
Style Transfer (HP)
|
89% |
1760
2.28 IPS |
|
|
Style Transfer (Q)
|
98% |
3621
4.67 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
523
19.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
526
19.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
868
32.2 IPS |
|
|
Text Classification (SP)
|
100% |
246
327.8 IPS |
|
|
Text Classification (HP)
|
100% |
244
325.9 IPS |
|
|
Text Classification (Q)
|
88% |
509
686.8 IPS |
|
|
Machine Translation (SP)
|
100% |
434
7.48 IPS |
|
|
Machine Translation (HP)
|
100% |
428
7.37 IPS |
|
|
Machine Translation (Q)
|
50% |
328
11.6 IPS |
