samsung SM-A166W
Geekbench AI Score
174
Single Precision Score
170
Half Precision Score
477
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 14 2026 10:54 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
122
22.6 IPS |
|
|
Image Classification (HP)
|
100% |
122
22.7 IPS |
|
|
Image Classification (Q)
|
99% |
329
61.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
167
2.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
168
2.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
373
6.07 IPS |
|
|
Pose Estimation (SP)
|
100% |
219
0.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
201
0.24 IPS |
|
|
Pose Estimation (Q)
|
98% |
828
0.97 IPS |
|
|
Object Detection (SP)
|
100% |
122
9.65 IPS |
|
|
Object Detection (HP)
|
100% |
118
9.36 IPS |
|
|
Object Detection (Q)
|
87% |
345
27.7 IPS |
|
|
Face Detection (SP)
|
100% |
308
3.66 IPS |
|
|
Face Detection (HP)
|
100% |
311
3.69 IPS |
|
|
Face Detection (Q)
|
97% |
684
8.16 IPS |
|
|
Depth Estimation (SP)
|
100% |
264
2.04 IPS |
|
|
Depth Estimation (HP)
|
99% |
256
1.97 IPS |
|
|
Depth Estimation (Q)
|
64% |
607
5.51 IPS |
|
|
Style Transfer (SP)
|
100% |
102
0.13 IPS |
|
|
Style Transfer (HP)
|
100% |
95
0.12 IPS |
|
|
Style Transfer (Q)
|
98% |
1080
1.39 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
121
4.48 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
123
4.54 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
436
16.2 IPS |
|
|
Text Classification (SP)
|
100% |
163
217.8 IPS |
|
|
Text Classification (HP)
|
100% |
164
219.3 IPS |
|
|
Text Classification (Q)
|
91% |
325
436.3 IPS |
|
|
Machine Translation (SP)
|
100% |
295
5.09 IPS |
|
|
Machine Translation (HP)
|
100% |
279
4.81 IPS |
|
|
Machine Translation (Q)
|
57% |
275
6.71 IPS |
