samsung SM-A166W
Geekbench AI Score
319
Single Precision Score
543
Half Precision Score
461
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 24 2025 08:01 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
195
36.4 IPS |
|
|
Image Classification (HP)
|
100% |
349
64.8 IPS |
|
|
Image Classification (Q)
|
97% |
307
57.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
562
9.11 IPS |
|
|
Image Segmentation (Q)
|
98% |
532
8.64 IPS |
|
|
Pose Estimation (SP)
|
100% |
1132
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2121
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2093
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
313
24.8 IPS |
|
|
Object Detection (Q)
|
83% |
296
23.9 IPS |
|
|
Face Detection (SP)
|
100% |
621
7.37 IPS |
|
|
Face Detection (HP)
|
100% |
1176
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1256
15.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
785
6.05 IPS |
|
|
Depth Estimation (HP)
|
98% |
1473
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1148
10.9 IPS |
|
|
Style Transfer (SP)
|
100% |
1829
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
4047
5.20 IPS |
|
|
Style Transfer (Q)
|
98% |
3979
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
421
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
810
29.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
747
27.7 IPS |
|
|
Text Classification (SP)
|
35% |
11
96.4 IPS |
|
|
Text Classification (HP)
|
29% |
9
160.9 IPS |
|
|
Text Classification (Q)
|
32% |
12
157.8 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (HP)
|
100% |
338
5.82 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.86 IPS |
