samsung SM-A166W
Geekbench AI Score
502
Single Precision Score
497
Half Precision Score
953
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 03 2025 11:52 AM |
| Views | 2 |
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% |
244
45.4 IPS |
|
|
Image Classification (HP)
|
100% |
247
45.9 IPS |
|
|
Image Classification (Q)
|
100% |
769
142.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
308
4.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
310
5.03 IPS |
|
|
Image Segmentation (Q)
|
98% |
870
14.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1195
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1186
1.38 IPS |
|
|
Pose Estimation (Q)
|
84% |
1741
2.07 IPS |
|
|
Object Detection (SP)
|
100% |
230
18.3 IPS |
|
|
Object Detection (HP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (Q)
|
83% |
673
54.4 IPS |
|
|
Face Detection (SP)
|
100% |
688
8.17 IPS |
|
|
Face Detection (HP)
|
100% |
769
9.13 IPS |
|
|
Face Detection (Q)
|
95% |
1667
19.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
986
7.60 IPS |
|
|
Depth Estimation (HP)
|
99% |
889
6.85 IPS |
|
|
Depth Estimation (Q)
|
64% |
1410
12.9 IPS |
|
|
Style Transfer (SP)
|
89% |
1875
2.43 IPS |
|
|
Style Transfer (HP)
|
89% |
1731
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
2893
3.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
406
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
420
15.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
817
30.3 IPS |
|
|
Text Classification (SP)
|
100% |
233
311.6 IPS |
|
|
Text Classification (HP)
|
100% |
229
305.6 IPS |
|
|
Text Classification (Q)
|
88% |
451
607.8 IPS |
|
|
Machine Translation (SP)
|
100% |
417
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
392
6.76 IPS |
|
|
Machine Translation (Q)
|
50% |
315
11.2 IPS |
