samsung SM-A166W
Geekbench AI Score
327
Single Precision Score
544
Half Precision Score
453
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 10 2026 12:24 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% |
189
35.1 IPS |
|
|
Image Classification (HP)
|
100% |
338
62.9 IPS |
|
|
Image Classification (Q)
|
97% |
324
60.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
566
9.18 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1132
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2127
2.48 IPS |
|
|
Pose Estimation (Q)
|
95% |
2081
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
324
25.7 IPS |
|
|
Object Detection (Q)
|
83% |
294
23.8 IPS |
|
|
Face Detection (SP)
|
100% |
596
7.08 IPS |
|
|
Face Detection (HP)
|
100% |
1182
14.0 IPS |
|
|
Face Detection (Q)
|
96% |
1002
11.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
772
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1486
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1158
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1830
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
3990
5.13 IPS |
|
|
Style Transfer (Q)
|
98% |
3995
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
423
15.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
763
28.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
761
28.2 IPS |
|
|
Text Classification (SP)
|
35% |
15
137.6 IPS |
|
|
Text Classification (HP)
|
29% |
10
171.7 IPS |
|
|
Text Classification (Q)
|
32% |
12
156.9 IPS |
|
|
Machine Translation (SP)
|
100% |
261
4.50 IPS |
|
|
Machine Translation (HP)
|
100% |
327
5.63 IPS |
|
|
Machine Translation (Q)
|
43% |
82
4.80 IPS |
