samsung SM-A166W
Geekbench AI Score
314
Single Precision Score
542
Half Precision Score
457
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 27 2025 06:53 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
171
31.7 IPS |
|
|
Image Classification (HP)
|
100% |
339
63.1 IPS |
|
|
Image Classification (Q)
|
97% |
318
59.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
553
8.96 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1135
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2107
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2082
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
320
25.4 IPS |
|
|
Object Detection (Q)
|
83% |
299
24.1 IPS |
|
|
Face Detection (SP)
|
100% |
586
6.96 IPS |
|
|
Face Detection (HP)
|
100% |
1197
14.2 IPS |
|
|
Face Detection (Q)
|
96% |
1029
12.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
772
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1507
11.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
1160
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1835
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4029
5.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3999
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
419
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
802
29.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
743
27.5 IPS |
|
|
Text Classification (SP)
|
35% |
11
96.9 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.6 IPS |
|
|
Text Classification (Q)
|
32% |
13
162.7 IPS |
|
|
Machine Translation (SP)
|
100% |
268
4.62 IPS |
|
|
Machine Translation (HP)
|
100% |
335
5.77 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.84 IPS |
