samsung SM-A166W
Geekbench AI Score
477
Single Precision Score
466
Half Precision Score
861
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 27 2025 03:41 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
237
44.1 IPS |
|
|
Image Classification (HP)
|
100% |
234
43.5 IPS |
|
|
Image Classification (Q)
|
100% |
607
112.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
285
4.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
285
4.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
768
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1118
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
987
1.15 IPS |
|
|
Pose Estimation (Q)
|
84% |
1562
1.85 IPS |
|
|
Object Detection (SP)
|
100% |
210
16.6 IPS |
|
|
Object Detection (HP)
|
100% |
202
16.1 IPS |
|
|
Object Detection (Q)
|
83% |
573
46.3 IPS |
|
|
Face Detection (SP)
|
100% |
724
8.60 IPS |
|
|
Face Detection (HP)
|
100% |
730
8.67 IPS |
|
|
Face Detection (Q)
|
95% |
1450
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
859
6.62 IPS |
|
|
Depth Estimation (HP)
|
99% |
868
6.69 IPS |
|
|
Depth Estimation (Q)
|
64% |
1194
10.9 IPS |
|
|
Style Transfer (SP)
|
89% |
1676
2.18 IPS |
|
|
Style Transfer (HP)
|
89% |
1583
2.06 IPS |
|
|
Style Transfer (Q)
|
98% |
3234
4.17 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
421
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
446
16.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
765
28.4 IPS |
|
|
Text Classification (SP)
|
100% |
221
295.2 IPS |
|
|
Text Classification (HP)
|
100% |
218
291.3 IPS |
|
|
Text Classification (Q)
|
88% |
455
613.8 IPS |
|
|
Machine Translation (SP)
|
100% |
404
6.96 IPS |
|
|
Machine Translation (HP)
|
100% |
375
6.46 IPS |
|
|
Machine Translation (Q)
|
50% |
276
9.81 IPS |
