samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
503
Half Precision Score
417
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 14 2025 02:26 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
209
38.8 IPS |
|
|
Image Classification (HP)
|
100% |
391
72.8 IPS |
|
|
Image Classification (Q)
|
97% |
339
63.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
273
4.42 IPS |
|
|
Image Segmentation (HP)
|
100% |
593
9.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
556
9.05 IPS |
|
|
Pose Estimation (SP)
|
100% |
1149
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
2162
2.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
2131
2.50 IPS |
|
|
Object Detection (SP)
|
100% |
187
14.9 IPS |
|
|
Object Detection (HP)
|
99% |
369
29.3 IPS |
|
|
Object Detection (Q)
|
83% |
345
27.8 IPS |
|
|
Face Detection (SP)
|
100% |
660
7.84 IPS |
|
|
Face Detection (HP)
|
100% |
1300
15.4 IPS |
|
|
Face Detection (Q)
|
96% |
1122
13.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
830
6.39 IPS |
|
|
Depth Estimation (HP)
|
98% |
1567
12.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
1237
11.8 IPS |
|
|
Style Transfer (SP)
|
100% |
1843
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4057
5.22 IPS |
|
|
Style Transfer (Q)
|
98% |
4036
5.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
470
17.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
854
31.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
836
31.0 IPS |
|
|
Text Classification (SP)
|
35% |
11
99.8 IPS |
|
|
Text Classification (HP)
|
29% |
4
60.6 IPS |
|
|
Text Classification (Q)
|
32% |
5
64.6 IPS |
|
|
Machine Translation (SP)
|
100% |
168
2.90 IPS |
|
|
Machine Translation (HP)
|
100% |
200
3.45 IPS |
|
|
Machine Translation (Q)
|
43% |
49
2.86 IPS |
