samsung SM-A166W
Geekbench AI Score
309
Single Precision Score
528
Half Precision Score
452
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 18 2025 02:49 AM |
| Views | 6 |
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% |
176
32.7 IPS |
|
|
Image Classification (HP)
|
100% |
327
60.9 IPS |
|
|
Image Classification (Q)
|
97% |
304
56.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
547
8.87 IPS |
|
|
Image Segmentation (Q)
|
98% |
534
8.68 IPS |
|
|
Pose Estimation (SP)
|
100% |
1127
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2090
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
321
25.4 IPS |
|
|
Object Detection (Q)
|
83% |
303
24.5 IPS |
|
|
Face Detection (SP)
|
100% |
604
7.18 IPS |
|
|
Face Detection (HP)
|
100% |
1168
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1042
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
793
6.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
1515
11.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
1170
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1830
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
4013
5.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3976
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
423
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
747
27.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
748
27.7 IPS |
|
|
Text Classification (SP)
|
35% |
9
86.1 IPS |
|
|
Text Classification (HP)
|
29% |
8
146.5 IPS |
|
|
Text Classification (Q)
|
32% |
12
158.7 IPS |
|
|
Machine Translation (SP)
|
100% |
256
4.41 IPS |
|
|
Machine Translation (HP)
|
100% |
328
5.65 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.71 IPS |
