samsung SM-A166W
Geekbench AI Score
477
Single Precision Score
473
Half Precision Score
878
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 10 2025 02:24 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
237
44.0 IPS |
|
|
Image Classification (HP)
|
100% |
233
43.4 IPS |
|
|
Image Classification (Q)
|
100% |
746
138.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
293
4.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
285
4.63 IPS |
|
|
Image Segmentation (Q)
|
98% |
774
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1126
1.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
1056
1.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
1416
1.68 IPS |
|
|
Object Detection (SP)
|
100% |
204
16.2 IPS |
|
|
Object Detection (HP)
|
100% |
203
16.1 IPS |
|
|
Object Detection (Q)
|
83% |
581
46.9 IPS |
|
|
Face Detection (SP)
|
100% |
658
7.82 IPS |
|
|
Face Detection (HP)
|
100% |
624
7.41 IPS |
|
|
Face Detection (Q)
|
95% |
1302
15.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
872
6.72 IPS |
|
|
Depth Estimation (HP)
|
99% |
787
6.07 IPS |
|
|
Depth Estimation (Q)
|
64% |
1035
9.48 IPS |
|
|
Style Transfer (SP)
|
89% |
1286
1.67 IPS |
|
|
Style Transfer (HP)
|
89% |
1686
2.19 IPS |
|
|
Style Transfer (Q)
|
98% |
3592
4.63 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
524
19.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
505
18.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
834
30.9 IPS |
|
|
Text Classification (SP)
|
100% |
236
315.1 IPS |
|
|
Text Classification (HP)
|
100% |
228
304.9 IPS |
|
|
Text Classification (Q)
|
88% |
444
598.9 IPS |
|
|
Machine Translation (SP)
|
100% |
419
7.22 IPS |
|
|
Machine Translation (HP)
|
100% |
416
7.16 IPS |
|
|
Machine Translation (Q)
|
50% |
321
11.4 IPS |
