samsung SM-A166W
Geekbench AI Score
535
Single Precision Score
526
Half Precision Score
1036
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 24 2025 07:53 PM |
| Views | 9 |
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% |
235
43.7 IPS |
|
|
Image Classification (HP)
|
100% |
245
45.5 IPS |
|
|
Image Classification (Q)
|
100% |
769
143.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
312
5.06 IPS |
|
|
Image Segmentation (HP)
|
100% |
312
5.06 IPS |
|
|
Image Segmentation (Q)
|
98% |
874
14.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1189
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1168
1.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
1770
2.10 IPS |
|
|
Object Detection (SP)
|
100% |
230
18.3 IPS |
|
|
Object Detection (HP)
|
100% |
231
18.3 IPS |
|
|
Object Detection (Q)
|
83% |
728
58.8 IPS |
|
|
Face Detection (SP)
|
100% |
781
9.28 IPS |
|
|
Face Detection (HP)
|
100% |
788
9.36 IPS |
|
|
Face Detection (Q)
|
95% |
1726
20.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1042
8.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
937
7.22 IPS |
|
|
Depth Estimation (Q)
|
64% |
1539
14.1 IPS |
|
|
Style Transfer (SP)
|
89% |
1935
2.51 IPS |
|
|
Style Transfer (HP)
|
89% |
1848
2.40 IPS |
|
|
Style Transfer (Q)
|
98% |
3938
5.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
528
19.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
542
20.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
896
33.2 IPS |
|
|
Text Classification (SP)
|
100% |
257
343.1 IPS |
|
|
Text Classification (HP)
|
100% |
250
333.0 IPS |
|
|
Text Classification (Q)
|
88% |
532
717.2 IPS |
|
|
Machine Translation (SP)
|
100% |
456
7.85 IPS |
|
|
Machine Translation (HP)
|
100% |
431
7.43 IPS |
|
|
Machine Translation (Q)
|
50% |
331
11.8 IPS |
