samsung SM-A166W
Geekbench AI Score
495
Single Precision Score
504
Half Precision Score
955
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | M91 |
| Upload Date | January 27 2026 12:34 PM |
| 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% |
232
43.1 IPS |
|
|
Image Classification (HP)
|
100% |
219
40.7 IPS |
|
|
Image Classification (Q)
|
100% |
550
102.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
242
3.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
282
4.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
777
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1177
1.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1145
1.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
1701
2.02 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
100% |
219
17.4 IPS |
|
|
Object Detection (Q)
|
83% |
637
51.4 IPS |
|
|
Face Detection (SP)
|
100% |
691
8.21 IPS |
|
|
Face Detection (HP)
|
100% |
790
9.38 IPS |
|
|
Face Detection (Q)
|
95% |
1653
19.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
907
6.99 IPS |
|
|
Depth Estimation (HP)
|
99% |
926
7.13 IPS |
|
|
Depth Estimation (Q)
|
64% |
1396
12.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1747
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1760
2.28 IPS |
|
|
Style Transfer (Q)
|
98% |
3713
4.79 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
487
18.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
485
17.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
903
33.5 IPS |
|
|
Text Classification (SP)
|
100% |
258
344.8 IPS |
|
|
Text Classification (HP)
|
100% |
256
341.1 IPS |
|
|
Text Classification (Q)
|
88% |
534
720.7 IPS |
|
|
Machine Translation (SP)
|
100% |
434
7.48 IPS |
|
|
Machine Translation (HP)
|
100% |
429
7.40 IPS |
|
|
Machine Translation (Q)
|
50% |
330
11.7 IPS |
