samsung SM-A166W
Geekbench AI Score
522
Single Precision Score
915
Half Precision Score
1063
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 01 2026 07:53 AM |
| Views | 5 |
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% |
233
43.3 IPS |
|
|
Image Classification (HP)
|
100% |
485
90.1 IPS |
|
|
Image Classification (Q)
|
99% |
702
131.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
296
4.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
543
8.80 IPS |
|
|
Image Segmentation (Q)
|
98% |
809
13.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1188
1.39 IPS |
|
|
Pose Estimation (HP)
|
92% |
2368
2.78 IPS |
|
|
Pose Estimation (Q)
|
96% |
1773
2.08 IPS |
|
|
Object Detection (SP)
|
100% |
230
18.3 IPS |
|
|
Object Detection (HP)
|
97% |
462
36.7 IPS |
|
|
Object Detection (Q)
|
85% |
691
55.7 IPS |
|
|
Face Detection (SP)
|
100% |
706
8.39 IPS |
|
|
Face Detection (HP)
|
100% |
1264
15.0 IPS |
|
|
Face Detection (Q)
|
97% |
1673
19.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1027
7.91 IPS |
|
|
Depth Estimation (HP)
|
98% |
1719
13.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
1534
14.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1865
2.42 IPS |
|
|
Style Transfer (HP)
|
88% |
2597
3.37 IPS |
|
|
Style Transfer (Q)
|
98% |
3762
4.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
487
18.0 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
930
34.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
967
35.8 IPS |
|
|
Text Classification (SP)
|
100% |
273
364.9 IPS |
|
|
Text Classification (HP)
|
100% |
440
587.6 IPS |
|
|
Text Classification (Q)
|
93% |
583
782.9 IPS |
|
|
Machine Translation (SP)
|
100% |
449
7.73 IPS |
|
|
Machine Translation (HP)
|
96% |
619
10.7 IPS |
|
|
Machine Translation (Q)
|
55% |
488
13.1 IPS |
