samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
544
Half Precision Score
443
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 01 2025 12:07 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% |
193
36.0 IPS |
|
|
Image Classification (HP)
|
100% |
336
62.5 IPS |
|
|
Image Classification (Q)
|
97% |
308
57.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
272
4.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
567
9.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
554
9.01 IPS |
|
|
Pose Estimation (SP)
|
100% |
1128
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2141
2.50 IPS |
|
|
Pose Estimation (Q)
|
95% |
2088
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
324
25.7 IPS |
|
|
Object Detection (Q)
|
83% |
299
24.1 IPS |
|
|
Face Detection (SP)
|
100% |
609
7.24 IPS |
|
|
Face Detection (HP)
|
100% |
1175
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1012
12.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
768
5.92 IPS |
|
|
Depth Estimation (HP)
|
98% |
1461
11.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
1164
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4027
5.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3992
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
457
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
742
27.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
778
28.8 IPS |
|
|
Text Classification (SP)
|
35% |
10
93.5 IPS |
|
|
Text Classification (HP)
|
29% |
10
167.4 IPS |
|
|
Text Classification (Q)
|
29% |
9
154.1 IPS |
|
|
Machine Translation (SP)
|
100% |
263
4.53 IPS |
|
|
Machine Translation (HP)
|
100% |
339
5.84 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.87 IPS |
