samsung SM-A166W
Geekbench AI Score
498
Single Precision Score
497
Half Precision Score
938
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 21 2025 06:11 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
229
42.6 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.5 IPS |
|
|
Image Classification (Q)
|
100% |
758
141.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
306
4.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
290
4.70 IPS |
|
|
Image Segmentation (Q)
|
98% |
763
12.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1170
1.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1116
1.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
1640
1.94 IPS |
|
|
Object Detection (SP)
|
100% |
220
17.4 IPS |
|
|
Object Detection (HP)
|
100% |
219
17.4 IPS |
|
|
Object Detection (Q)
|
83% |
630
50.9 IPS |
|
|
Face Detection (SP)
|
100% |
702
8.34 IPS |
|
|
Face Detection (HP)
|
100% |
741
8.80 IPS |
|
|
Face Detection (Q)
|
95% |
1508
18.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
914
7.04 IPS |
|
|
Depth Estimation (HP)
|
99% |
889
6.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
1332
12.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1730
2.25 IPS |
|
|
Style Transfer (HP)
|
89% |
1727
2.24 IPS |
|
|
Style Transfer (Q)
|
98% |
3441
4.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
470
17.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
471
17.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
818
30.3 IPS |
|
|
Text Classification (SP)
|
100% |
235
313.0 IPS |
|
|
Text Classification (HP)
|
100% |
244
326.1 IPS |
|
|
Text Classification (Q)
|
88% |
505
680.5 IPS |
|
|
Machine Translation (SP)
|
100% |
432
7.44 IPS |
|
|
Machine Translation (HP)
|
100% |
420
7.23 IPS |
|
|
Machine Translation (Q)
|
50% |
312
11.1 IPS |
