samsung SM-A166W
Geekbench AI Score
562
Single Precision Score
1006
Half Precision Score
1176
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 29 2026 09:30 AM |
| Views | 5 |
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% |
252
46.8 IPS |
|
|
Image Classification (HP)
|
100% |
496
92.2 IPS |
|
|
Image Classification (Q)
|
99% |
764
142.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
322
5.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
610
9.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
896
14.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1190
1.39 IPS |
|
|
Pose Estimation (HP)
|
92% |
2373
2.79 IPS |
|
|
Pose Estimation (Q)
|
96% |
1858
2.18 IPS |
|
|
Object Detection (SP)
|
100% |
233
18.5 IPS |
|
|
Object Detection (HP)
|
97% |
474
37.7 IPS |
|
|
Object Detection (Q)
|
85% |
752
60.6 IPS |
|
|
Face Detection (SP)
|
100% |
790
9.39 IPS |
|
|
Face Detection (HP)
|
100% |
1457
17.3 IPS |
|
|
Face Detection (Q)
|
97% |
1816
21.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1069
8.24 IPS |
|
|
Depth Estimation (HP)
|
98% |
1997
15.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
1730
16.0 IPS |
|
|
Style Transfer (SP)
|
89% |
2012
2.61 IPS |
|
|
Style Transfer (HP)
|
88% |
2908
3.78 IPS |
|
|
Style Transfer (Q)
|
98% |
4277
5.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
563
20.8 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1056
39.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1067
39.6 IPS |
|
|
Text Classification (SP)
|
100% |
307
410.4 IPS |
|
|
Text Classification (HP)
|
100% |
510
680.2 IPS |
|
|
Text Classification (Q)
|
93% |
670
899.2 IPS |
|
|
Machine Translation (SP)
|
100% |
477
8.22 IPS |
|
|
Machine Translation (HP)
|
96% |
690
11.9 IPS |
|
|
Machine Translation (Q)
|
55% |
551
14.8 IPS |
