samsung SM-A166W
Geekbench AI Score
431
Single Precision Score
416
Half Precision Score
792
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 07 2025 11:40 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
230
42.8 IPS |
|
|
Image Classification (HP)
|
100% |
212
39.5 IPS |
|
|
Image Classification (Q)
|
100% |
638
118.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
274
4.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
284
4.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
758
12.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
990
1.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
889
1.04 IPS |
|
|
Pose Estimation (Q)
|
84% |
1346
1.60 IPS |
|
|
Object Detection (SP)
|
100% |
181
14.4 IPS |
|
|
Object Detection (HP)
|
100% |
174
13.8 IPS |
|
|
Object Detection (Q)
|
83% |
519
41.9 IPS |
|
|
Face Detection (SP)
|
100% |
605
7.19 IPS |
|
|
Face Detection (HP)
|
100% |
606
7.20 IPS |
|
|
Face Detection (Q)
|
95% |
1239
14.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
688
5.30 IPS |
|
|
Depth Estimation (Q)
|
64% |
1121
10.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1466
1.90 IPS |
|
|
Style Transfer (HP)
|
89% |
1358
1.76 IPS |
|
|
Style Transfer (Q)
|
98% |
2852
3.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
422
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
427
15.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
683
25.3 IPS |
|
|
Text Classification (SP)
|
100% |
193
256.9 IPS |
|
|
Text Classification (HP)
|
100% |
210
280.2 IPS |
|
|
Text Classification (Q)
|
88% |
433
583.5 IPS |
|
|
Machine Translation (SP)
|
100% |
360
6.20 IPS |
|
|
Machine Translation (HP)
|
100% |
336
5.79 IPS |
|
|
Machine Translation (Q)
|
50% |
247
8.75 IPS |
