samsung SM-A166W
Geekbench AI Score
491
Single Precision Score
491
Half Precision Score
920
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 12 2025 02:41 AM |
| Views | 2 |
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% |
236
43.8 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.4 IPS |
|
|
Image Classification (Q)
|
100% |
760
141.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
299
4.85 IPS |
|
|
Image Segmentation (HP)
|
100% |
286
4.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
766
12.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1187
1.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1111
1.30 IPS |
|
|
Pose Estimation (Q)
|
84% |
1576
1.87 IPS |
|
|
Object Detection (SP)
|
100% |
204
16.2 IPS |
|
|
Object Detection (HP)
|
100% |
205
16.2 IPS |
|
|
Object Detection (Q)
|
83% |
613
49.5 IPS |
|
|
Face Detection (SP)
|
100% |
668
7.93 IPS |
|
|
Face Detection (HP)
|
100% |
739
8.78 IPS |
|
|
Face Detection (Q)
|
95% |
1526
18.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
871
6.71 IPS |
|
|
Depth Estimation (HP)
|
99% |
893
6.88 IPS |
|
|
Depth Estimation (Q)
|
64% |
1273
11.7 IPS |
|
|
Style Transfer (SP)
|
89% |
1749
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1736
2.25 IPS |
|
|
Style Transfer (Q)
|
98% |
3461
4.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
462
17.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
484
17.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
818
30.3 IPS |
|
|
Text Classification (SP)
|
100% |
235
313.5 IPS |
|
|
Text Classification (HP)
|
100% |
233
310.7 IPS |
|
|
Text Classification (Q)
|
88% |
490
660.6 IPS |
|
|
Machine Translation (SP)
|
100% |
433
7.47 IPS |
|
|
Machine Translation (HP)
|
100% |
410
7.06 IPS |
|
|
Machine Translation (Q)
|
50% |
289
10.3 IPS |
