samsung SM-A166W
Geekbench AI Score
539
Single Precision Score
527
Half Precision Score
1042
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 27 2025 06:46 PM |
| Views | 10 |
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% |
242
45.0 IPS |
|
|
Image Classification (HP)
|
100% |
236
43.9 IPS |
|
|
Image Classification (Q)
|
100% |
770
143.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
308
5.00 IPS |
|
|
Image Segmentation (HP)
|
100% |
313
5.07 IPS |
|
|
Image Segmentation (Q)
|
98% |
880
14.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1184
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1193
1.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
1787
2.12 IPS |
|
|
Object Detection (SP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (HP)
|
100% |
230
18.2 IPS |
|
|
Object Detection (Q)
|
83% |
743
60.0 IPS |
|
|
Face Detection (SP)
|
100% |
776
9.22 IPS |
|
|
Face Detection (HP)
|
100% |
782
9.29 IPS |
|
|
Face Detection (Q)
|
95% |
1728
20.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1043
8.04 IPS |
|
|
Depth Estimation (HP)
|
99% |
1023
7.88 IPS |
|
|
Depth Estimation (Q)
|
64% |
1612
14.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1928
2.50 IPS |
|
|
Style Transfer (HP)
|
89% |
1855
2.41 IPS |
|
|
Style Transfer (Q)
|
98% |
3935
5.07 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
546
20.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
496
18.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
858
31.8 IPS |
|
|
Text Classification (SP)
|
100% |
265
353.9 IPS |
|
|
Text Classification (HP)
|
100% |
264
351.9 IPS |
|
|
Text Classification (Q)
|
88% |
562
758.1 IPS |
|
|
Machine Translation (SP)
|
100% |
459
7.91 IPS |
|
|
Machine Translation (HP)
|
100% |
421
7.24 IPS |
|
|
Machine Translation (Q)
|
50% |
320
11.4 IPS |
