samsung SM-A166W
Geekbench AI Score
495
Single Precision Score
489
Half Precision Score
913
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 07:23 PM |
| Views | 5 |
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
43.1 IPS |
|
|
Image Classification (HP)
|
100% |
232
43.2 IPS |
|
|
Image Classification (Q)
|
100% |
641
119.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
275
4.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
293
4.74 IPS |
|
|
Image Segmentation (Q)
|
98% |
803
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1174
1.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1112
1.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
1644
1.95 IPS |
|
|
Object Detection (SP)
|
100% |
212
16.8 IPS |
|
|
Object Detection (HP)
|
100% |
213
16.9 IPS |
|
|
Object Detection (Q)
|
83% |
634
51.2 IPS |
|
|
Face Detection (SP)
|
100% |
744
8.84 IPS |
|
|
Face Detection (HP)
|
100% |
756
8.98 IPS |
|
|
Face Detection (Q)
|
95% |
1521
18.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
889
6.85 IPS |
|
|
Depth Estimation (HP)
|
99% |
858
6.61 IPS |
|
|
Depth Estimation (Q)
|
64% |
1269
11.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1703
2.21 IPS |
|
|
Style Transfer (HP)
|
89% |
1679
2.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3391
4.37 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
497
18.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
472
17.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
813
30.1 IPS |
|
|
Text Classification (SP)
|
100% |
239
318.4 IPS |
|
|
Text Classification (HP)
|
100% |
235
313.8 IPS |
|
|
Text Classification (Q)
|
88% |
488
658.0 IPS |
|
|
Machine Translation (SP)
|
100% |
421
7.26 IPS |
|
|
Machine Translation (HP)
|
100% |
402
6.92 IPS |
|
|
Machine Translation (Q)
|
50% |
289
10.3 IPS |
