samsung SM-A166W
Geekbench AI Score
317
Single Precision Score
544
Half Precision Score
450
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 07:30 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
184
34.2 IPS |
|
|
Image Classification (HP)
|
100% |
324
60.3 IPS |
|
|
Image Classification (Q)
|
97% |
306
57.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
560
9.07 IPS |
|
|
Image Segmentation (Q)
|
98% |
530
8.62 IPS |
|
|
Pose Estimation (SP)
|
100% |
1134
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2121
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2083
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
314
24.9 IPS |
|
|
Object Detection (Q)
|
83% |
295
23.8 IPS |
|
|
Face Detection (SP)
|
100% |
608
7.22 IPS |
|
|
Face Detection (HP)
|
100% |
1298
15.4 IPS |
|
|
Face Detection (Q)
|
96% |
1036
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
773
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1478
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1163
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1829
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
3988
5.13 IPS |
|
|
Style Transfer (Q)
|
98% |
3997
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
422
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
830
30.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
735
27.2 IPS |
|
|
Text Classification (SP)
|
35% |
11
98.3 IPS |
|
|
Text Classification (HP)
|
29% |
9
157.7 IPS |
|
|
Text Classification (Q)
|
32% |
12
155.0 IPS |
|
|
Machine Translation (SP)
|
100% |
262
4.51 IPS |
|
|
Machine Translation (HP)
|
100% |
333
5.74 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.72 IPS |
