samsung SM-A166W
Geekbench AI Score
499
Single Precision Score
497
Half Precision Score
932
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 25 2025 02:33 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
232
43.1 IPS |
|
|
Image Classification (HP)
|
100% |
236
44.0 IPS |
|
|
Image Classification (Q)
|
100% |
672
124.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
282
4.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
288
4.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
797
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1116
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
1089
1.27 IPS |
|
|
Pose Estimation (Q)
|
84% |
1559
1.85 IPS |
|
|
Object Detection (SP)
|
100% |
219
17.4 IPS |
|
|
Object Detection (HP)
|
100% |
207
16.4 IPS |
|
|
Object Detection (Q)
|
83% |
603
48.7 IPS |
|
|
Face Detection (SP)
|
100% |
721
8.56 IPS |
|
|
Face Detection (HP)
|
100% |
742
8.81 IPS |
|
|
Face Detection (Q)
|
95% |
1452
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
899
6.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
905
6.97 IPS |
|
|
Depth Estimation (Q)
|
64% |
1396
12.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1749
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1728
2.24 IPS |
|
|
Style Transfer (Q)
|
98% |
3611
4.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
472
17.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
514
19.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
856
31.7 IPS |
|
|
Text Classification (SP)
|
100% |
251
334.4 IPS |
|
|
Text Classification (HP)
|
100% |
244
325.0 IPS |
|
|
Text Classification (Q)
|
88% |
502
677.0 IPS |
|
|
Machine Translation (SP)
|
100% |
447
7.70 IPS |
|
|
Machine Translation (HP)
|
100% |
414
7.13 IPS |
|
|
Machine Translation (Q)
|
50% |
313
11.1 IPS |
