samsung SM-A166W
Geekbench AI Score
318
Single Precision Score
550
Half Precision Score
460
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 16 2025 01:39 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
186
34.6 IPS |
|
|
Image Classification (HP)
|
100% |
345
64.2 IPS |
|
|
Image Classification (Q)
|
97% |
311
58.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
565
9.16 IPS |
|
|
Image Segmentation (Q)
|
98% |
547
8.89 IPS |
|
|
Pose Estimation (SP)
|
100% |
1145
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2080
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
321
25.4 IPS |
|
|
Object Detection (Q)
|
83% |
297
24.0 IPS |
|
|
Face Detection (SP)
|
100% |
620
7.37 IPS |
|
|
Face Detection (HP)
|
100% |
1172
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1050
12.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.94 IPS |
|
|
Depth Estimation (HP)
|
98% |
1485
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1187
11.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4100
5.27 IPS |
|
|
Style Transfer (Q)
|
98% |
3993
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
420
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
753
27.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
744
27.6 IPS |
|
|
Text Classification (SP)
|
35% |
10
94.6 IPS |
|
|
Text Classification (HP)
|
29% |
10
177.9 IPS |
|
|
Text Classification (Q)
|
32% |
13
166.3 IPS |
|
|
Machine Translation (SP)
|
100% |
289
4.97 IPS |
|
|
Machine Translation (HP)
|
100% |
357
6.16 IPS |
|
|
Machine Translation (Q)
|
43% |
85
4.94 IPS |
