samsung SM-A166W
Geekbench AI Score
319
Single Precision Score
537
Half Precision Score
449
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 06 2025 12:18 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
184
34.3 IPS |
|
|
Image Classification (HP)
|
100% |
341
63.5 IPS |
|
|
Image Classification (Q)
|
97% |
292
54.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
268
4.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
541
8.77 IPS |
|
|
Image Segmentation (Q)
|
98% |
533
8.66 IPS |
|
|
Pose Estimation (SP)
|
100% |
1133
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2122
2.48 IPS |
|
|
Pose Estimation (Q)
|
95% |
2108
2.47 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
317
25.1 IPS |
|
|
Object Detection (Q)
|
83% |
298
24.1 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
1175
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
994
11.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
791
6.10 IPS |
|
|
Depth Estimation (HP)
|
98% |
1482
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1158
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1831
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
4015
5.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3986
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
448
16.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
784
29.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
744
27.6 IPS |
|
|
Text Classification (SP)
|
35% |
11
97.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
152.6 IPS |
|
|
Text Classification (Q)
|
32% |
12
159.0 IPS |
|
|
Machine Translation (SP)
|
100% |
262
4.52 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.68 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.91 IPS |
