samsung SM-A166W
Geekbench AI Score
474
Single Precision Score
460
Half Precision Score
884
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 15 2025 08:36 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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
42.7 IPS |
|
|
Image Classification (HP)
|
100% |
230
42.7 IPS |
|
|
Image Classification (Q)
|
100% |
739
137.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
237
3.85 IPS |
|
|
Image Segmentation (HP)
|
100% |
256
4.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
676
11.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1157
1.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
1082
1.26 IPS |
|
|
Pose Estimation (Q)
|
84% |
1599
1.90 IPS |
|
|
Object Detection (SP)
|
100% |
222
17.6 IPS |
|
|
Object Detection (HP)
|
100% |
210
16.7 IPS |
|
|
Object Detection (Q)
|
83% |
611
49.3 IPS |
|
|
Face Detection (SP)
|
100% |
642
7.63 IPS |
|
|
Face Detection (HP)
|
100% |
657
7.80 IPS |
|
|
Face Detection (Q)
|
95% |
1461
17.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
901
6.94 IPS |
|
|
Depth Estimation (HP)
|
99% |
866
6.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
1261
11.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1694
2.20 IPS |
|
|
Style Transfer (HP)
|
89% |
1663
2.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3264
4.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
477
17.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
423
15.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
763
28.3 IPS |
|
|
Text Classification (SP)
|
100% |
219
292.6 IPS |
|
|
Text Classification (HP)
|
100% |
218
290.8 IPS |
|
|
Text Classification (Q)
|
88% |
460
620.9 IPS |
|
|
Machine Translation (SP)
|
100% |
402
6.93 IPS |
|
|
Machine Translation (HP)
|
100% |
366
6.31 IPS |
|
|
Machine Translation (Q)
|
50% |
285
10.1 IPS |
