samsung SM-A166W
Geekbench AI Score
499
Single Precision Score
885
Half Precision Score
1016
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 08 2026 09:31 AM |
| Views | 6 |
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% |
226
42.0 IPS |
|
|
Image Classification (HP)
|
100% |
485
90.3 IPS |
|
|
Image Classification (Q)
|
99% |
756
140.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
285
4.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
550
8.91 IPS |
|
|
Image Segmentation (Q)
|
98% |
791
12.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
1169
1.36 IPS |
|
|
Pose Estimation (HP)
|
92% |
2254
2.65 IPS |
|
|
Pose Estimation (Q)
|
96% |
1729
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
227
18.0 IPS |
|
|
Object Detection (HP)
|
97% |
454
36.1 IPS |
|
|
Object Detection (Q)
|
85% |
637
51.3 IPS |
|
|
Face Detection (SP)
|
100% |
678
8.06 IPS |
|
|
Face Detection (HP)
|
100% |
1244
14.8 IPS |
|
|
Face Detection (Q)
|
97% |
1615
19.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
917
7.07 IPS |
|
|
Depth Estimation (HP)
|
98% |
1733
13.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
1410
13.0 IPS |
|
|
Style Transfer (SP)
|
89% |
1816
2.36 IPS |
|
|
Style Transfer (HP)
|
88% |
2431
3.16 IPS |
|
|
Style Transfer (Q)
|
98% |
3641
4.69 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
473
17.5 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
871
32.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
872
32.3 IPS |
|
|
Text Classification (SP)
|
100% |
249
331.7 IPS |
|
|
Text Classification (HP)
|
100% |
406
542.3 IPS |
|
|
Text Classification (Q)
|
93% |
531
712.3 IPS |
|
|
Machine Translation (SP)
|
100% |
428
7.37 IPS |
|
|
Machine Translation (HP)
|
96% |
587
10.1 IPS |
|
|
Machine Translation (Q)
|
55% |
466
12.5 IPS |
