samsung SM-A166W
Geekbench AI Score
168
Single Precision Score
163
Half Precision Score
445
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 08 2026 10:07 AM |
| Views | 9 |
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% |
119
22.2 IPS |
|
|
Image Classification (HP)
|
100% |
120
22.3 IPS |
|
|
Image Classification (Q)
|
99% |
329
61.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
168
2.72 IPS |
|
|
Image Segmentation (HP)
|
100% |
169
2.74 IPS |
|
|
Image Segmentation (Q)
|
98% |
374
6.08 IPS |
|
|
Pose Estimation (SP)
|
100% |
211
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
185
0.22 IPS |
|
|
Pose Estimation (Q)
|
98% |
792
0.93 IPS |
|
|
Object Detection (SP)
|
100% |
111
8.80 IPS |
|
|
Object Detection (HP)
|
100% |
93
7.40 IPS |
|
|
Object Detection (Q)
|
87% |
276
22.1 IPS |
|
|
Face Detection (SP)
|
100% |
278
3.30 IPS |
|
|
Face Detection (HP)
|
100% |
272
3.23 IPS |
|
|
Face Detection (Q)
|
97% |
592
7.05 IPS |
|
|
Depth Estimation (SP)
|
100% |
237
1.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
235
1.81 IPS |
|
|
Depth Estimation (Q)
|
64% |
577
5.23 IPS |
|
|
Style Transfer (SP)
|
100% |
120
0.15 IPS |
|
|
Style Transfer (HP)
|
100% |
121
0.16 IPS |
|
|
Style Transfer (Q)
|
98% |
1056
1.36 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
113
4.18 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
122
4.50 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
405
15.0 IPS |
|
|
Text Classification (SP)
|
100% |
157
210.1 IPS |
|
|
Text Classification (HP)
|
100% |
157
210.2 IPS |
|
|
Text Classification (Q)
|
91% |
300
403.4 IPS |
|
|
Machine Translation (SP)
|
100% |
279
4.80 IPS |
|
|
Machine Translation (HP)
|
100% |
271
4.67 IPS |
|
|
Machine Translation (Q)
|
57% |
262
6.41 IPS |
