samsung SM-A166W
Geekbench AI Score
323
Single Precision Score
567
Half Precision Score
482
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | December 16 2025 04:01 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
181
33.7 IPS |
|
|
Image Classification (HP)
|
100% |
333
61.9 IPS |
|
|
Image Classification (Q)
|
97% |
319
59.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
550
8.91 IPS |
|
|
Image Segmentation (Q)
|
98% |
525
8.53 IPS |
|
|
Pose Estimation (SP)
|
100% |
1135
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2111
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2083
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
317
25.1 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.7 IPS |
|
|
Face Detection (SP)
|
100% |
624
7.41 IPS |
|
|
Face Detection (HP)
|
100% |
1417
16.8 IPS |
|
|
Face Detection (Q)
|
96% |
1248
14.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
833
6.42 IPS |
|
|
Depth Estimation (HP)
|
98% |
1596
12.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
1274
12.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1889
2.43 IPS |
|
|
Style Transfer (HP)
|
100% |
4164
5.35 IPS |
|
|
Style Transfer (Q)
|
98% |
4050
5.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
455
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
888
32.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
874
32.4 IPS |
|
|
Text Classification (SP)
|
35% |
11
100.5 IPS |
|
|
Text Classification (HP)
|
29% |
10
168.6 IPS |
|
|
Text Classification (Q)
|
33% |
15
163.1 IPS |
|
|
Machine Translation (SP)
|
100% |
259
4.46 IPS |
|
|
Machine Translation (HP)
|
100% |
341
5.88 IPS |
|
|
Machine Translation (Q)
|
43% |
80
4.67 IPS |
