samsung SM-A166W
Geekbench AI Score
313
Single Precision Score
549
Half Precision Score
455
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 18 2025 02:04 AM |
| Views | 4 |
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% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
336
62.5 IPS |
|
|
Image Classification (Q)
|
97% |
305
56.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
272
4.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
558
9.05 IPS |
|
|
Image Segmentation (Q)
|
98% |
538
8.74 IPS |
|
|
Pose Estimation (SP)
|
100% |
1142
1.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
2117
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2087
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
319
25.3 IPS |
|
|
Object Detection (Q)
|
83% |
312
25.2 IPS |
|
|
Face Detection (SP)
|
100% |
614
7.29 IPS |
|
|
Face Detection (HP)
|
100% |
1267
15.1 IPS |
|
|
Face Detection (Q)
|
96% |
1041
12.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.89 IPS |
|
|
Depth Estimation (HP)
|
98% |
1476
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1161
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1836
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4019
5.17 IPS |
|
|
Style Transfer (Q)
|
98% |
3976
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
418
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
768
28.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
740
27.4 IPS |
|
|
Text Classification (SP)
|
35% |
10
87.5 IPS |
|
|
Text Classification (HP)
|
29% |
10
173.4 IPS |
|
|
Text Classification (Q)
|
32% |
12
160.0 IPS |
|
|
Machine Translation (SP)
|
100% |
264
4.55 IPS |
|
|
Machine Translation (HP)
|
100% |
346
5.96 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.88 IPS |
