samsung SM-A166W
Geekbench AI Score
459
Single Precision Score
444
Half Precision Score
834
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 28 2025 11:13 AM |
| Views | 13 |
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% |
237
44.1 IPS |
|
|
Image Classification (HP)
|
100% |
233
43.3 IPS |
|
|
Image Classification (Q)
|
100% |
744
138.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
283
4.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
276
4.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
741
12.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1050
1.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
921
1.07 IPS |
|
|
Pose Estimation (Q)
|
84% |
1384
1.64 IPS |
|
|
Object Detection (SP)
|
100% |
204
16.1 IPS |
|
|
Object Detection (HP)
|
100% |
194
15.4 IPS |
|
|
Object Detection (Q)
|
83% |
571
46.1 IPS |
|
|
Face Detection (SP)
|
100% |
674
8.01 IPS |
|
|
Face Detection (HP)
|
100% |
582
6.91 IPS |
|
|
Face Detection (Q)
|
95% |
1161
13.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
798
6.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
749
5.77 IPS |
|
|
Depth Estimation (Q)
|
64% |
1123
10.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1490
1.93 IPS |
|
|
Style Transfer (HP)
|
89% |
1486
1.93 IPS |
|
|
Style Transfer (Q)
|
98% |
3046
3.93 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
444
16.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
467
17.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
769
28.5 IPS |
|
|
Text Classification (SP)
|
100% |
224
299.2 IPS |
|
|
Text Classification (HP)
|
100% |
217
290.1 IPS |
|
|
Text Classification (Q)
|
88% |
450
606.3 IPS |
|
|
Machine Translation (SP)
|
100% |
370
6.38 IPS |
|
|
Machine Translation (HP)
|
100% |
398
6.86 IPS |
|
|
Machine Translation (Q)
|
50% |
275
9.75 IPS |
