samsung SM-A166W
Geekbench AI Score
471
Single Precision Score
451
Half Precision Score
869
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 04 2025 02:11 AM |
| Views | 6 |
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% |
232
43.1 IPS |
|
|
Image Classification (HP)
|
100% |
203
37.8 IPS |
|
|
Image Classification (Q)
|
100% |
585
108.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
265
4.30 IPS |
|
|
Image Segmentation (HP)
|
100% |
286
4.63 IPS |
|
|
Image Segmentation (Q)
|
98% |
770
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1098
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1027
1.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
1564
1.86 IPS |
|
|
Object Detection (SP)
|
100% |
203
16.1 IPS |
|
|
Object Detection (HP)
|
100% |
204
16.2 IPS |
|
|
Object Detection (Q)
|
83% |
575
46.4 IPS |
|
|
Face Detection (SP)
|
100% |
693
8.23 IPS |
|
|
Face Detection (HP)
|
100% |
658
7.82 IPS |
|
|
Face Detection (Q)
|
95% |
1438
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
886
6.82 IPS |
|
|
Depth Estimation (HP)
|
99% |
865
6.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
1201
11.0 IPS |
|
|
Style Transfer (SP)
|
89% |
1737
2.26 IPS |
|
|
Style Transfer (HP)
|
89% |
1553
2.02 IPS |
|
|
Style Transfer (Q)
|
98% |
3428
4.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
455
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
452
16.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
807
29.9 IPS |
|
|
Text Classification (SP)
|
100% |
207
276.9 IPS |
|
|
Text Classification (HP)
|
100% |
206
275.4 IPS |
|
|
Text Classification (Q)
|
88% |
468
630.8 IPS |
|
|
Machine Translation (SP)
|
100% |
391
6.73 IPS |
|
|
Machine Translation (HP)
|
100% |
355
6.11 IPS |
|
|
Machine Translation (Q)
|
50% |
272
9.67 IPS |
