samsung SM-A166W
Geekbench AI Score
537
Single Precision Score
957
Half Precision Score
1116
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 31 2026 08:49 PM |
| 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% |
236
43.9 IPS |
|
|
Image Classification (HP)
|
100% |
494
91.8 IPS |
|
|
Image Classification (Q)
|
99% |
772
143.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
311
5.04 IPS |
|
|
Image Segmentation (HP)
|
100% |
597
9.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
871
14.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1165
1.36 IPS |
|
|
Pose Estimation (HP)
|
92% |
2342
2.75 IPS |
|
|
Pose Estimation (Q)
|
96% |
1797
2.11 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
97% |
461
36.7 IPS |
|
|
Object Detection (Q)
|
85% |
747
60.2 IPS |
|
|
Face Detection (SP)
|
100% |
776
9.22 IPS |
|
|
Face Detection (HP)
|
100% |
1442
17.1 IPS |
|
|
Face Detection (Q)
|
97% |
1794
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1038
8.00 IPS |
|
|
Depth Estimation (HP)
|
98% |
1970
15.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
1605
14.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1971
2.56 IPS |
|
|
Style Transfer (HP)
|
88% |
2622
3.40 IPS |
|
|
Style Transfer (Q)
|
98% |
3917
5.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
495
18.3 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
916
34.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1003
37.2 IPS |
|
|
Text Classification (SP)
|
100% |
279
372.0 IPS |
|
|
Text Classification (HP)
|
100% |
467
623.6 IPS |
|
|
Text Classification (Q)
|
93% |
603
809.4 IPS |
|
|
Machine Translation (SP)
|
100% |
475
8.18 IPS |
|
|
Machine Translation (HP)
|
96% |
640
11.1 IPS |
|
|
Machine Translation (Q)
|
55% |
487
13.1 IPS |
