samsung SM-A166W
Geekbench AI Score
497
Single Precision Score
874
Half Precision Score
1001
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 15 2026 10:42 AM |
| Views | 10 |
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% |
233
43.4 IPS |
|
|
Image Classification (HP)
|
100% |
481
89.5 IPS |
|
|
Image Classification (Q)
|
99% |
714
133.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
267
4.32 IPS |
|
|
Image Segmentation (HP)
|
100% |
527
8.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
776
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1112
1.30 IPS |
|
|
Pose Estimation (HP)
|
92% |
2239
2.63 IPS |
|
|
Pose Estimation (Q)
|
96% |
1731
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
223
17.7 IPS |
|
|
Object Detection (HP)
|
97% |
408
32.5 IPS |
|
|
Object Detection (Q)
|
85% |
612
49.3 IPS |
|
|
Face Detection (SP)
|
100% |
725
8.62 IPS |
|
|
Face Detection (HP)
|
100% |
1332
15.8 IPS |
|
|
Face Detection (Q)
|
97% |
1546
18.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
931
7.17 IPS |
|
|
Depth Estimation (HP)
|
98% |
1730
13.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
1477
13.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1793
2.33 IPS |
|
|
Style Transfer (HP)
|
88% |
2308
3.00 IPS |
|
|
Style Transfer (Q)
|
98% |
3464
4.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
466
17.2 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
880
32.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
872
32.3 IPS |
|
|
Text Classification (SP)
|
100% |
249
331.8 IPS |
|
|
Text Classification (HP)
|
100% |
410
547.2 IPS |
|
|
Text Classification (Q)
|
93% |
541
726.6 IPS |
|
|
Machine Translation (SP)
|
100% |
431
7.43 IPS |
|
|
Machine Translation (HP)
|
96% |
587
10.1 IPS |
|
|
Machine Translation (Q)
|
55% |
463
12.4 IPS |
