samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
537
Half Precision Score
461
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 17 2025 02:55 AM |
| Views | 7 |
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% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
346
64.4 IPS |
|
|
Image Classification (Q)
|
97% |
337
62.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
544
8.82 IPS |
|
|
Image Segmentation (Q)
|
98% |
529
8.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
1128
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2116
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2085
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
318
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.7 IPS |
|
|
Face Detection (SP)
|
100% |
614
7.30 IPS |
|
|
Face Detection (HP)
|
100% |
1168
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1028
12.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.93 IPS |
|
|
Depth Estimation (HP)
|
98% |
1470
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1157
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4018
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
3998
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
415
15.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
776
28.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
864
32.0 IPS |
|
|
Text Classification (SP)
|
35% |
12
104.7 IPS |
|
|
Text Classification (HP)
|
29% |
9
156.2 IPS |
|
|
Text Classification (Q)
|
32% |
12
156.3 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.67 IPS |
|
|
Machine Translation (Q)
|
43% |
82
4.79 IPS |
