samsung SM-A166W
Geekbench AI Score
506
Single Precision Score
507
Half Precision Score
967
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 10 2026 12:01 PM |
| Views | 8 |
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% |
240
44.6 IPS |
|
|
Image Classification (HP)
|
100% |
241
44.8 IPS |
|
|
Image Classification (Q)
|
100% |
696
129.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
290
4.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
294
4.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
797
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1186
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1130
1.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
1711
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
221
17.5 IPS |
|
|
Object Detection (HP)
|
100% |
218
17.3 IPS |
|
|
Object Detection (Q)
|
83% |
663
53.6 IPS |
|
|
Face Detection (SP)
|
100% |
697
8.28 IPS |
|
|
Face Detection (HP)
|
100% |
746
8.86 IPS |
|
|
Face Detection (Q)
|
95% |
1514
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
888
6.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
915
7.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
1414
12.9 IPS |
|
|
Style Transfer (SP)
|
89% |
1887
2.45 IPS |
|
|
Style Transfer (HP)
|
89% |
1731
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
3733
4.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
479
17.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
535
19.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
863
32.0 IPS |
|
|
Text Classification (SP)
|
100% |
245
327.6 IPS |
|
|
Text Classification (HP)
|
100% |
244
326.1 IPS |
|
|
Text Classification (Q)
|
88% |
514
693.1 IPS |
|
|
Machine Translation (SP)
|
100% |
446
7.68 IPS |
|
|
Machine Translation (HP)
|
100% |
420
7.23 IPS |
|
|
Machine Translation (Q)
|
50% |
322
11.4 IPS |
