samsung SM-A166W
Geekbench AI Score
315
Single Precision Score
542
Half Precision Score
454
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 08 2026 09:38 AM |
| Views | 5 |
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% |
339
63.0 IPS |
|
|
Image Classification (Q)
|
97% |
311
58.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
553
8.97 IPS |
|
|
Image Segmentation (Q)
|
98% |
533
8.67 IPS |
|
|
Pose Estimation (SP)
|
100% |
1133
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2119
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2149
2.52 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
340
27.0 IPS |
|
|
Object Detection (Q)
|
83% |
298
24.1 IPS |
|
|
Face Detection (SP)
|
100% |
619
7.36 IPS |
|
|
Face Detection (HP)
|
100% |
1174
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1016
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
789
6.08 IPS |
|
|
Depth Estimation (HP)
|
98% |
1490
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1178
11.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1834
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4007
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3987
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
423
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
784
29.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
752
27.9 IPS |
|
|
Text Classification (SP)
|
35% |
10
87.1 IPS |
|
|
Text Classification (HP)
|
29% |
9
155.9 IPS |
|
|
Text Classification (Q)
|
32% |
12
156.8 IPS |
|
|
Machine Translation (SP)
|
100% |
263
4.52 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.66 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.83 IPS |
