samsung SM-A166W
Geekbench AI Score
321
Single Precision Score
538
Half Precision Score
450
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 22 2026 08:35 AM |
| 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% |
185
34.4 IPS |
|
|
Image Classification (HP)
|
100% |
331
61.5 IPS |
|
|
Image Classification (Q)
|
97% |
303
56.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
552
8.95 IPS |
|
|
Image Segmentation (Q)
|
98% |
524
8.52 IPS |
|
|
Pose Estimation (SP)
|
100% |
1123
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2108
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2121
2.49 IPS |
|
|
Object Detection (SP)
|
100% |
178
14.1 IPS |
|
|
Object Detection (HP)
|
99% |
322
25.5 IPS |
|
|
Object Detection (Q)
|
83% |
292
23.6 IPS |
|
|
Face Detection (SP)
|
100% |
627
7.45 IPS |
|
|
Face Detection (HP)
|
100% |
1181
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1020
12.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
764
5.88 IPS |
|
|
Depth Estimation (HP)
|
98% |
1472
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1161
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1836
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
3996
5.14 IPS |
|
|
Style Transfer (Q)
|
98% |
3967
5.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
408
15.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
783
28.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
742
27.5 IPS |
|
|
Text Classification (SP)
|
35% |
10
91.5 IPS |
|
|
Text Classification (HP)
|
29% |
9
147.5 IPS |
|
|
Text Classification (Q)
|
32% |
12
161.1 IPS |
|
|
Machine Translation (SP)
|
100% |
328
5.64 IPS |
|
|
Machine Translation (HP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.89 IPS |
