samsung SM-A166W
Geekbench AI Score
522
Single Precision Score
525
Half Precision Score
1002
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 31 2025 02:28 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
246
45.7 IPS |
|
|
Image Classification (HP)
|
100% |
245
45.5 IPS |
|
|
Image Classification (Q)
|
100% |
771
143.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
314
5.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
314
5.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
860
14.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1192
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1169
1.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
1782
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (HP)
|
100% |
229
18.1 IPS |
|
|
Object Detection (Q)
|
83% |
665
53.7 IPS |
|
|
Face Detection (SP)
|
100% |
770
9.15 IPS |
|
|
Face Detection (HP)
|
100% |
769
9.14 IPS |
|
|
Face Detection (Q)
|
95% |
1601
19.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
941
7.25 IPS |
|
|
Depth Estimation (HP)
|
99% |
972
7.49 IPS |
|
|
Depth Estimation (Q)
|
64% |
1486
13.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1739
2.26 IPS |
|
|
Style Transfer (HP)
|
89% |
1821
2.36 IPS |
|
|
Style Transfer (Q)
|
98% |
3767
4.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
488
18.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
538
19.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
905
33.5 IPS |
|
|
Text Classification (SP)
|
100% |
262
350.3 IPS |
|
|
Text Classification (HP)
|
100% |
247
329.2 IPS |
|
|
Text Classification (Q)
|
88% |
512
690.1 IPS |
|
|
Machine Translation (SP)
|
100% |
448
7.72 IPS |
|
|
Machine Translation (HP)
|
100% |
430
7.41 IPS |
|
|
Machine Translation (Q)
|
50% |
314
11.2 IPS |
