samsung SM-A166W
Geekbench AI Score
317
Single Precision Score
536
Half Precision Score
457
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 07 2025 11:47 PM |
| Views | 9 |
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% |
192
35.6 IPS |
|
|
Image Classification (HP)
|
100% |
343
63.9 IPS |
|
|
Image Classification (Q)
|
97% |
323
60.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
559
9.06 IPS |
|
|
Image Segmentation (Q)
|
98% |
530
8.61 IPS |
|
|
Pose Estimation (SP)
|
100% |
1130
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2117
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2087
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
310
24.6 IPS |
|
|
Object Detection (Q)
|
83% |
297
24.0 IPS |
|
|
Face Detection (SP)
|
100% |
598
7.10 IPS |
|
|
Face Detection (HP)
|
100% |
1168
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1056
12.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
766
5.91 IPS |
|
|
Depth Estimation (HP)
|
98% |
1479
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1170
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4045
5.20 IPS |
|
|
Style Transfer (Q)
|
98% |
3995
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
418
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
752
27.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
785
29.1 IPS |
|
|
Text Classification (SP)
|
35% |
11
103.1 IPS |
|
|
Text Classification (HP)
|
29% |
9
158.3 IPS |
|
|
Text Classification (Q)
|
32% |
12
154.4 IPS |
|
|
Machine Translation (SP)
|
100% |
263
4.53 IPS |
|
|
Machine Translation (HP)
|
100% |
334
5.75 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.70 IPS |
