samsung SM-A166W
Geekbench AI Score
511
Single Precision Score
503
Half Precision Score
972
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 06 2025 12:11 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
240
44.7 IPS |
|
|
Image Classification (Q)
|
100% |
698
129.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
290
4.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
292
4.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
798
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1182
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1170
1.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
1781
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
220
17.5 IPS |
|
|
Object Detection (HP)
|
100% |
220
17.5 IPS |
|
|
Object Detection (Q)
|
83% |
659
53.2 IPS |
|
|
Face Detection (SP)
|
100% |
768
9.13 IPS |
|
|
Face Detection (HP)
|
100% |
765
9.09 IPS |
|
|
Face Detection (Q)
|
95% |
1517
18.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
910
7.01 IPS |
|
|
Depth Estimation (HP)
|
99% |
929
7.16 IPS |
|
|
Depth Estimation (Q)
|
64% |
1472
13.5 IPS |
|
|
Style Transfer (SP)
|
89% |
1803
2.34 IPS |
|
|
Style Transfer (HP)
|
89% |
1735
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
3549
4.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
482
17.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
482
17.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
876
32.4 IPS |
|
|
Text Classification (SP)
|
100% |
248
331.3 IPS |
|
|
Text Classification (HP)
|
100% |
242
322.7 IPS |
|
|
Text Classification (Q)
|
88% |
525
708.7 IPS |
|
|
Machine Translation (SP)
|
100% |
445
7.66 IPS |
|
|
Machine Translation (HP)
|
100% |
407
7.01 IPS |
|
|
Machine Translation (Q)
|
50% |
317
11.3 IPS |
