samsung SM-A166W
Geekbench AI Score
508
Single Precision Score
506
Half Precision Score
973
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 10 2025 10:07 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
233
43.3 IPS |
|
|
Image Classification (HP)
|
100% |
236
43.9 IPS |
|
|
Image Classification (Q)
|
100% |
756
140.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
308
4.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
309
5.00 IPS |
|
|
Image Segmentation (Q)
|
98% |
874
14.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1181
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1127
1.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
1636
1.94 IPS |
|
|
Object Detection (SP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (HP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (Q)
|
83% |
669
54.1 IPS |
|
|
Face Detection (SP)
|
100% |
747
8.88 IPS |
|
|
Face Detection (HP)
|
100% |
721
8.57 IPS |
|
|
Face Detection (Q)
|
95% |
1526
18.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
905
6.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
891
6.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
1415
13.0 IPS |
|
|
Style Transfer (SP)
|
89% |
1741
2.26 IPS |
|
|
Style Transfer (HP)
|
89% |
1738
2.26 IPS |
|
|
Style Transfer (Q)
|
98% |
3607
4.65 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
476
17.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
520
19.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
875
32.4 IPS |
|
|
Text Classification (SP)
|
100% |
244
325.4 IPS |
|
|
Text Classification (HP)
|
100% |
236
314.5 IPS |
|
|
Text Classification (Q)
|
88% |
485
653.7 IPS |
|
|
Machine Translation (SP)
|
100% |
437
7.53 IPS |
|
|
Machine Translation (HP)
|
100% |
432
7.44 IPS |
|
|
Machine Translation (Q)
|
50% |
319
11.3 IPS |
