samsung SM-A166W
Geekbench AI Score
543
Single Precision Score
544
Half Precision Score
1060
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 01 2025 12:00 PM |
| Views | 7 |
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% |
248
46.2 IPS |
|
|
Image Classification (HP)
|
100% |
241
44.8 IPS |
|
|
Image Classification (Q)
|
100% |
770
143.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
313
5.07 IPS |
|
|
Image Segmentation (HP)
|
100% |
315
5.11 IPS |
|
|
Image Segmentation (Q)
|
98% |
870
14.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1195
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1181
1.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
1800
2.13 IPS |
|
|
Object Detection (SP)
|
100% |
233
18.5 IPS |
|
|
Object Detection (HP)
|
100% |
232
18.4 IPS |
|
|
Object Detection (Q)
|
83% |
741
59.9 IPS |
|
|
Face Detection (SP)
|
100% |
782
9.29 IPS |
|
|
Face Detection (HP)
|
100% |
783
9.30 IPS |
|
|
Face Detection (Q)
|
95% |
1778
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1060
8.17 IPS |
|
|
Depth Estimation (HP)
|
99% |
1072
8.26 IPS |
|
|
Depth Estimation (Q)
|
64% |
1704
15.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1934
2.51 IPS |
|
|
Style Transfer (HP)
|
89% |
1876
2.44 IPS |
|
|
Style Transfer (Q)
|
98% |
3912
5.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
510
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
574
21.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
962
35.6 IPS |
|
|
Text Classification (SP)
|
100% |
271
361.8 IPS |
|
|
Text Classification (HP)
|
100% |
264
352.7 IPS |
|
|
Text Classification (Q)
|
88% |
559
753.5 IPS |
|
|
Machine Translation (SP)
|
100% |
469
8.08 IPS |
|
|
Machine Translation (HP)
|
100% |
462
7.95 IPS |
|
|
Machine Translation (Q)
|
50% |
317
11.2 IPS |
