samsung SM-A166W
Geekbench AI Score
494
Single Precision Score
480
Half Precision Score
923
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 10 2025 02:43 AM |
| Views | 8 |
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% |
239
44.5 IPS |
|
|
Image Classification (HP)
|
100% |
236
43.9 IPS |
|
|
Image Classification (Q)
|
100% |
757
140.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
309
5.01 IPS |
|
|
Image Segmentation (HP)
|
100% |
274
4.43 IPS |
|
|
Image Segmentation (Q)
|
98% |
727
11.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1121
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
1093
1.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
1634
1.94 IPS |
|
|
Object Detection (SP)
|
100% |
218
17.3 IPS |
|
|
Object Detection (HP)
|
100% |
214
16.9 IPS |
|
|
Object Detection (Q)
|
83% |
613
49.5 IPS |
|
|
Face Detection (SP)
|
100% |
698
8.30 IPS |
|
|
Face Detection (HP)
|
100% |
661
7.85 IPS |
|
|
Face Detection (Q)
|
95% |
1519
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
892
6.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
892
6.87 IPS |
|
|
Depth Estimation (Q)
|
64% |
1393
12.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1721
2.23 IPS |
|
|
Style Transfer (HP)
|
89% |
1665
2.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3484
4.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
459
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
478
17.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
818
30.3 IPS |
|
|
Text Classification (SP)
|
100% |
237
316.2 IPS |
|
|
Text Classification (HP)
|
100% |
233
310.4 IPS |
|
|
Text Classification (Q)
|
88% |
485
654.4 IPS |
|
|
Machine Translation (SP)
|
100% |
416
7.17 IPS |
|
|
Machine Translation (HP)
|
100% |
395
6.81 IPS |
|
|
Machine Translation (Q)
|
50% |
279
9.89 IPS |
