samsung SM-A166W
Geekbench AI Score
550
Single Precision Score
968
Half Precision Score
1147
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 05 2026 12:09 AM |
| Views | 4 |
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% |
232
43.2 IPS |
|
|
Image Classification (HP)
|
100% |
495
92.1 IPS |
|
|
Image Classification (Q)
|
99% |
777
144.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
316
5.12 IPS |
|
|
Image Segmentation (HP)
|
100% |
589
9.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
886
14.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1183
1.38 IPS |
|
|
Pose Estimation (HP)
|
92% |
2367
2.78 IPS |
|
|
Pose Estimation (Q)
|
96% |
1817
2.13 IPS |
|
|
Object Detection (SP)
|
100% |
232
18.4 IPS |
|
|
Object Detection (HP)
|
97% |
467
37.2 IPS |
|
|
Object Detection (Q)
|
85% |
735
59.2 IPS |
|
|
Face Detection (SP)
|
100% |
784
9.31 IPS |
|
|
Face Detection (HP)
|
100% |
1458
17.3 IPS |
|
|
Face Detection (Q)
|
97% |
1793
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1057
8.14 IPS |
|
|
Depth Estimation (HP)
|
98% |
1956
15.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
1698
15.7 IPS |
|
|
Style Transfer (SP)
|
89% |
1990
2.58 IPS |
|
|
Style Transfer (HP)
|
88% |
2887
3.75 IPS |
|
|
Style Transfer (Q)
|
98% |
4316
5.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
573
21.2 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
940
34.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1006
37.3 IPS |
|
|
Text Classification (SP)
|
100% |
279
372.9 IPS |
|
|
Text Classification (HP)
|
100% |
463
618.3 IPS |
|
|
Text Classification (Q)
|
93% |
650
872.6 IPS |
|
|
Machine Translation (SP)
|
100% |
485
8.35 IPS |
|
|
Machine Translation (HP)
|
96% |
632
10.9 IPS |
|
|
Machine Translation (Q)
|
55% |
502
13.5 IPS |
