samsung SM-A166W
Geekbench AI Score
523
Single Precision Score
516
Half Precision Score
1008
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 28 2026 11:55 AM |
| Views | 6 |
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% |
240
44.6 IPS |
|
|
Image Classification (HP)
|
100% |
235
43.7 IPS |
|
|
Image Classification (Q)
|
100% |
761
141.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
311
5.04 IPS |
|
|
Image Segmentation (HP)
|
100% |
310
5.02 IPS |
|
|
Image Segmentation (Q)
|
98% |
870
14.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1179
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1172
1.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
1782
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (Q)
|
83% |
689
55.7 IPS |
|
|
Face Detection (SP)
|
100% |
700
8.32 IPS |
|
|
Face Detection (HP)
|
100% |
783
9.31 IPS |
|
|
Face Detection (Q)
|
95% |
1503
17.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
921
7.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
941
7.25 IPS |
|
|
Depth Estimation (Q)
|
64% |
1553
14.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1892
2.46 IPS |
|
|
Style Transfer (HP)
|
89% |
1821
2.36 IPS |
|
|
Style Transfer (Q)
|
98% |
3797
4.90 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
533
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
480
17.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
906
33.6 IPS |
|
|
Text Classification (SP)
|
100% |
259
345.5 IPS |
|
|
Text Classification (HP)
|
100% |
253
337.7 IPS |
|
|
Text Classification (Q)
|
88% |
526
709.4 IPS |
|
|
Machine Translation (SP)
|
100% |
457
7.87 IPS |
|
|
Machine Translation (HP)
|
100% |
422
7.27 IPS |
|
|
Machine Translation (Q)
|
50% |
318
11.3 IPS |
