samsung SM-A166W
Geekbench AI Score
311
Single Precision Score
540
Half Precision Score
455
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 08 2026 07:35 AM |
| Views | 8 |
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% |
169
31.4 IPS |
|
|
Image Classification (HP)
|
100% |
334
62.1 IPS |
|
|
Image Classification (Q)
|
97% |
312
58.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
557
9.03 IPS |
|
|
Image Segmentation (Q)
|
98% |
533
8.66 IPS |
|
|
Pose Estimation (SP)
|
100% |
1129
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2137
2.49 IPS |
|
|
Pose Estimation (Q)
|
95% |
2084
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
316
25.1 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.7 IPS |
|
|
Face Detection (SP)
|
100% |
634
7.54 IPS |
|
|
Face Detection (HP)
|
100% |
1207
14.3 IPS |
|
|
Face Detection (Q)
|
96% |
974
11.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
787
6.06 IPS |
|
|
Depth Estimation (HP)
|
98% |
1472
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1219
11.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1929
2.48 IPS |
|
|
Style Transfer (HP)
|
100% |
4088
5.26 IPS |
|
|
Style Transfer (Q)
|
98% |
3983
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
420
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
791
29.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
755
28.0 IPS |
|
|
Text Classification (SP)
|
35% |
9
83.6 IPS |
|
|
Text Classification (HP)
|
29% |
9
154.2 IPS |
|
|
Text Classification (Q)
|
32% |
13
164.1 IPS |
|
|
Machine Translation (SP)
|
100% |
260
4.47 IPS |
|
|
Machine Translation (HP)
|
100% |
329
5.66 IPS |
|
|
Machine Translation (Q)
|
43% |
82
4.76 IPS |
