samsung SM-A166W
Geekbench AI Score
314
Single Precision Score
559
Half Precision Score
470
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 13 2026 02:33 PM |
| Views | 3 |
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% |
181
33.6 IPS |
|
|
Image Classification (HP)
|
100% |
346
64.3 IPS |
|
|
Image Classification (Q)
|
97% |
307
57.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
593
9.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
576
9.37 IPS |
|
|
Pose Estimation (SP)
|
100% |
1127
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2120
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2085
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
179
14.2 IPS |
|
|
Object Detection (HP)
|
99% |
348
27.6 IPS |
|
|
Object Detection (Q)
|
83% |
319
25.8 IPS |
|
|
Face Detection (SP)
|
100% |
631
7.50 IPS |
|
|
Face Detection (HP)
|
100% |
1187
14.1 IPS |
|
|
Face Detection (Q)
|
96% |
1011
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
773
5.96 IPS |
|
|
Depth Estimation (HP)
|
98% |
1564
12.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
1172
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1832
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4036
5.19 IPS |
|
|
Style Transfer (Q)
|
98% |
4088
5.27 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
415
15.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
749
27.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
784
29.1 IPS |
|
|
Text Classification (SP)
|
35% |
10
94.7 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.8 IPS |
|
|
Text Classification (Q)
|
32% |
14
174.4 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (HP)
|
100% |
392
6.76 IPS |
|
|
Machine Translation (Q)
|
43% |
85
4.92 IPS |
