samsung SM-A166W
Geekbench AI Score
503
Single Precision Score
489
Half Precision Score
923
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 08 2026 07:28 AM |
| 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% |
241
44.7 IPS |
|
|
Image Classification (HP)
|
100% |
237
44.1 IPS |
|
|
Image Classification (Q)
|
100% |
648
120.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
286
4.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
286
4.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
868
14.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1183
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1135
1.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
1649
1.96 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
100% |
221
17.6 IPS |
|
|
Object Detection (Q)
|
83% |
640
51.7 IPS |
|
|
Face Detection (SP)
|
100% |
720
8.55 IPS |
|
|
Face Detection (HP)
|
100% |
743
8.83 IPS |
|
|
Face Detection (Q)
|
95% |
1427
17.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
887
6.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
838
6.46 IPS |
|
|
Depth Estimation (Q)
|
64% |
1336
12.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1762
2.29 IPS |
|
|
Style Transfer (HP)
|
89% |
1662
2.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3237
4.17 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
498
18.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
482
17.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
812
30.1 IPS |
|
|
Text Classification (SP)
|
100% |
238
318.1 IPS |
|
|
Text Classification (HP)
|
100% |
234
311.7 IPS |
|
|
Text Classification (Q)
|
88% |
483
651.5 IPS |
|
|
Machine Translation (SP)
|
100% |
425
7.32 IPS |
|
|
Machine Translation (HP)
|
100% |
401
6.91 IPS |
|
|
Machine Translation (Q)
|
50% |
314
11.1 IPS |
