samsung SM-A166W
Geekbench AI Score
308
Single Precision Score
536
Half Precision Score
454
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 02:18 AM |
| Views | 5 |
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% |
172
32.0 IPS |
|
|
Image Classification (HP)
|
100% |
335
62.2 IPS |
|
|
Image Classification (Q)
|
97% |
306
57.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
556
9.01 IPS |
|
|
Image Segmentation (Q)
|
98% |
528
8.59 IPS |
|
|
Pose Estimation (SP)
|
100% |
1137
1.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
2111
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2092
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
319
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
296
23.9 IPS |
|
|
Face Detection (SP)
|
100% |
615
7.31 IPS |
|
|
Face Detection (HP)
|
100% |
1174
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1010
12.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
779
6.00 IPS |
|
|
Depth Estimation (HP)
|
98% |
1477
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1158
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1835
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4010
5.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3996
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
407
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
752
27.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
738
27.3 IPS |
|
|
Text Classification (SP)
|
35% |
9
82.9 IPS |
|
|
Text Classification (HP)
|
29% |
9
153.0 IPS |
|
|
Text Classification (Q)
|
32% |
13
164.2 IPS |
|
|
Machine Translation (SP)
|
100% |
262
4.52 IPS |
|
|
Machine Translation (HP)
|
100% |
337
5.80 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.87 IPS |
