samsung SM-A166W
Geekbench AI Score
539
Single Precision Score
955
Half Precision Score
1114
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 12 2026 09:12 AM |
| Views | 7 |
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% |
485
90.2 IPS |
|
|
Image Classification (Q)
|
99% |
765
142.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
312
5.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
598
9.69 IPS |
|
|
Image Segmentation (Q)
|
98% |
879
14.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1191
1.39 IPS |
|
|
Pose Estimation (HP)
|
92% |
2372
2.79 IPS |
|
|
Pose Estimation (Q)
|
96% |
1807
2.12 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
97% |
466
37.1 IPS |
|
|
Object Detection (Q)
|
85% |
747
60.2 IPS |
|
|
Face Detection (SP)
|
100% |
791
9.40 IPS |
|
|
Face Detection (HP)
|
100% |
1434
17.0 IPS |
|
|
Face Detection (Q)
|
97% |
1800
21.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1052
8.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
1986
15.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
1658
15.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1927
2.50 IPS |
|
|
Style Transfer (HP)
|
88% |
2548
3.31 IPS |
|
|
Style Transfer (Q)
|
98% |
3970
5.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
509
18.8 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
950
35.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
993
36.8 IPS |
|
|
Text Classification (SP)
|
100% |
279
372.9 IPS |
|
|
Text Classification (HP)
|
100% |
457
609.9 IPS |
|
|
Text Classification (Q)
|
93% |
574
771.2 IPS |
|
|
Machine Translation (SP)
|
100% |
449
7.74 IPS |
|
|
Machine Translation (HP)
|
96% |
628
10.9 IPS |
|
|
Machine Translation (Q)
|
55% |
483
13.0 IPS |
