samsung SM-A166W
Geekbench AI Score
441
Single Precision Score
430
Half Precision Score
799
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 02 2025 02:50 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
237
44.1 IPS |
|
|
Image Classification (HP)
|
100% |
231
42.9 IPS |
|
|
Image Classification (Q)
|
100% |
698
129.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
274
4.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
271
4.40 IPS |
|
|
Image Segmentation (Q)
|
98% |
730
11.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1031
1.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
943
1.10 IPS |
|
|
Pose Estimation (Q)
|
84% |
1400
1.66 IPS |
|
|
Object Detection (SP)
|
100% |
182
14.5 IPS |
|
|
Object Detection (HP)
|
100% |
184
14.6 IPS |
|
|
Object Detection (Q)
|
83% |
517
41.8 IPS |
|
|
Face Detection (SP)
|
100% |
602
7.15 IPS |
|
|
Face Detection (HP)
|
100% |
594
7.06 IPS |
|
|
Face Detection (Q)
|
95% |
1153
13.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
685
5.28 IPS |
|
|
Depth Estimation (Q)
|
64% |
1113
10.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1486
1.93 IPS |
|
|
Style Transfer (HP)
|
89% |
1482
1.92 IPS |
|
|
Style Transfer (Q)
|
98% |
3056
3.94 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
429
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
441
16.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
685
25.4 IPS |
|
|
Text Classification (SP)
|
100% |
210
280.0 IPS |
|
|
Text Classification (HP)
|
100% |
213
284.5 IPS |
|
|
Text Classification (Q)
|
88% |
434
585.2 IPS |
|
|
Machine Translation (SP)
|
100% |
372
6.41 IPS |
|
|
Machine Translation (HP)
|
100% |
356
6.13 IPS |
|
|
Machine Translation (Q)
|
50% |
249
8.82 IPS |
