samsung SM-A166W
Geekbench AI Score
524
Single Precision Score
932
Half Precision Score
1085
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 14 2026 10:14 AM |
| Views | 3 |
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% |
239
44.4 IPS |
|
|
Image Classification (HP)
|
100% |
493
91.7 IPS |
|
|
Image Classification (Q)
|
99% |
718
134.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
294
4.77 IPS |
|
|
Image Segmentation (HP)
|
100% |
545
8.84 IPS |
|
|
Image Segmentation (Q)
|
98% |
820
13.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1184
1.38 IPS |
|
|
Pose Estimation (HP)
|
92% |
2377
2.79 IPS |
|
|
Pose Estimation (Q)
|
96% |
1804
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
231
18.3 IPS |
|
|
Object Detection (HP)
|
97% |
461
36.7 IPS |
|
|
Object Detection (Q)
|
85% |
752
60.6 IPS |
|
|
Face Detection (SP)
|
100% |
782
9.29 IPS |
|
|
Face Detection (HP)
|
100% |
1440
17.1 IPS |
|
|
Face Detection (Q)
|
97% |
1778
21.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
956
7.37 IPS |
|
|
Depth Estimation (HP)
|
98% |
1844
14.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
1555
14.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1843
2.39 IPS |
|
|
Style Transfer (HP)
|
88% |
2558
3.32 IPS |
|
|
Style Transfer (Q)
|
98% |
3765
4.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
496
18.3 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
894
33.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
977
36.2 IPS |
|
|
Text Classification (SP)
|
100% |
268
357.3 IPS |
|
|
Text Classification (HP)
|
100% |
447
596.9 IPS |
|
|
Text Classification (Q)
|
93% |
581
779.9 IPS |
|
|
Machine Translation (SP)
|
100% |
448
7.72 IPS |
|
|
Machine Translation (HP)
|
96% |
623
10.8 IPS |
|
|
Machine Translation (Q)
|
55% |
483
13.0 IPS |
