samsung SM-A166W
Geekbench AI Score
484
Single Precision Score
487
Half Precision Score
895
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 20 2025 03:36 AM |
| Views | 4 |
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% |
234
43.5 IPS |
|
|
Image Classification (HP)
|
100% |
234
43.6 IPS |
|
|
Image Classification (Q)
|
100% |
645
119.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
276
4.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
291
4.71 IPS |
|
|
Image Segmentation (Q)
|
98% |
773
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1083
1.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
1060
1.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
1562
1.85 IPS |
|
|
Object Detection (SP)
|
100% |
213
16.9 IPS |
|
|
Object Detection (HP)
|
100% |
211
16.8 IPS |
|
|
Object Detection (Q)
|
83% |
580
46.9 IPS |
|
|
Face Detection (SP)
|
100% |
726
8.63 IPS |
|
|
Face Detection (HP)
|
100% |
733
8.71 IPS |
|
|
Face Detection (Q)
|
95% |
1383
16.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
869
6.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
891
6.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
1339
12.3 IPS |
|
|
Style Transfer (SP)
|
89% |
1672
2.17 IPS |
|
|
Style Transfer (HP)
|
89% |
1559
2.02 IPS |
|
|
Style Transfer (Q)
|
98% |
3438
4.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
466
17.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
504
18.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
824
30.5 IPS |
|
|
Text Classification (SP)
|
100% |
234
312.7 IPS |
|
|
Text Classification (HP)
|
100% |
234
312.7 IPS |
|
|
Text Classification (Q)
|
88% |
489
658.9 IPS |
|
|
Machine Translation (SP)
|
100% |
420
7.23 IPS |
|
|
Machine Translation (HP)
|
100% |
412
7.09 IPS |
|
|
Machine Translation (Q)
|
50% |
285
10.1 IPS |
