samsung SM-A166W
Geekbench AI Score
309
Single Precision Score
537
Half Precision Score
450
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 12 2026 09:19 AM |
| Views | 6 |
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% |
177
32.9 IPS |
|
|
Image Classification (HP)
|
100% |
344
63.9 IPS |
|
|
Image Classification (Q)
|
97% |
300
56.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
552
8.95 IPS |
|
|
Image Segmentation (Q)
|
98% |
529
8.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
1124
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
2110
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2074
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
319
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
295
23.8 IPS |
|
|
Face Detection (SP)
|
100% |
610
7.25 IPS |
|
|
Face Detection (HP)
|
100% |
1195
14.2 IPS |
|
|
Face Detection (Q)
|
96% |
973
11.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
763
5.88 IPS |
|
|
Depth Estimation (HP)
|
98% |
1472
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1155
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1831
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
3999
5.14 IPS |
|
|
Style Transfer (Q)
|
98% |
3990
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
426
15.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
759
28.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
748
27.7 IPS |
|
|
Text Classification (SP)
|
35% |
9
84.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
151.8 IPS |
|
|
Text Classification (Q)
|
32% |
13
169.6 IPS |
|
|
Machine Translation (SP)
|
100% |
259
4.46 IPS |
|
|
Machine Translation (HP)
|
100% |
325
5.59 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.70 IPS |
