samsung SM-A166W
Geekbench AI Score
164
Single Precision Score
163
Half Precision Score
443
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 01 2026 08:32 AM |
| Views | 4 |
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
22.7 IPS |
|
|
Image Classification (HP)
|
100% |
122
22.7 IPS |
|
|
Image Classification (Q)
|
99% |
329
61.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
167
2.72 IPS |
|
|
Image Segmentation (HP)
|
100% |
169
2.74 IPS |
|
|
Image Segmentation (Q)
|
98% |
374
6.07 IPS |
|
|
Pose Estimation (SP)
|
100% |
215
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
194
0.23 IPS |
|
|
Pose Estimation (Q)
|
98% |
807
0.94 IPS |
|
|
Object Detection (SP)
|
100% |
115
9.08 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.03 IPS |
|
|
Object Detection (Q)
|
87% |
302
24.2 IPS |
|
|
Face Detection (SP)
|
100% |
290
3.44 IPS |
|
|
Face Detection (HP)
|
100% |
289
3.44 IPS |
|
|
Face Detection (Q)
|
97% |
641
7.64 IPS |
|
|
Depth Estimation (SP)
|
100% |
245
1.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
229
1.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
574
5.21 IPS |
|
|
Style Transfer (SP)
|
100% |
103
0.13 IPS |
|
|
Style Transfer (HP)
|
100% |
104
0.13 IPS |
|
|
Style Transfer (Q)
|
98% |
990
1.28 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
103
3.82 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
109
4.01 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
392
14.5 IPS |
|
|
Text Classification (SP)
|
100% |
151
202.1 IPS |
|
|
Text Classification (HP)
|
100% |
151
201.6 IPS |
|
|
Text Classification (Q)
|
91% |
286
384.9 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.48 IPS |
|
|
Machine Translation (HP)
|
100% |
261
4.49 IPS |
|
|
Machine Translation (Q)
|
57% |
242
5.92 IPS |
