samsung SM-A166W
Geekbench AI Score
327
Single Precision Score
563
Half Precision Score
470
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 14 2025 06:37 PM |
| Views | 5 |
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% |
201
37.3 IPS |
|
|
Image Classification (HP)
|
100% |
390
72.4 IPS |
|
|
Image Classification (Q)
|
97% |
353
65.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
275
4.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
586
9.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
554
9.01 IPS |
|
|
Pose Estimation (SP)
|
100% |
1150
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
2161
2.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
2153
2.52 IPS |
|
|
Object Detection (SP)
|
100% |
188
14.9 IPS |
|
|
Object Detection (HP)
|
99% |
368
29.2 IPS |
|
|
Object Detection (Q)
|
83% |
345
27.8 IPS |
|
|
Face Detection (SP)
|
100% |
658
7.82 IPS |
|
|
Face Detection (HP)
|
100% |
1312
15.6 IPS |
|
|
Face Detection (Q)
|
96% |
1147
13.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
826
6.36 IPS |
|
|
Depth Estimation (HP)
|
98% |
1569
12.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
1233
11.7 IPS |
|
|
Style Transfer (SP)
|
100% |
1843
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4056
5.21 IPS |
|
|
Style Transfer (Q)
|
98% |
4031
5.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
473
17.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
855
31.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
892
33.1 IPS |
|
|
Text Classification (SP)
|
35% |
15
138.4 IPS |
|
|
Text Classification (HP)
|
29% |
12
201.7 IPS |
|
|
Text Classification (Q)
|
32% |
13
167.9 IPS |
|
|
Machine Translation (SP)
|
100% |
169
2.92 IPS |
|
|
Machine Translation (HP)
|
100% |
206
3.55 IPS |
|
|
Machine Translation (Q)
|
43% |
55
3.19 IPS |
