samsung SM-A166W
Geekbench AI Score
311
Single Precision Score
549
Half Precision Score
455
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 31 2025 08:15 PM |
| Views | 6 |
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% |
190
35.3 IPS |
|
|
Image Classification (HP)
|
100% |
372
69.1 IPS |
|
|
Image Classification (Q)
|
97% |
327
61.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.39 IPS |
|
|
Image Segmentation (HP)
|
100% |
555
8.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
542
8.81 IPS |
|
|
Pose Estimation (SP)
|
100% |
1131
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2110
2.46 IPS |
|
|
Pose Estimation (Q)
|
95% |
2083
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
331
26.3 IPS |
|
|
Object Detection (Q)
|
83% |
295
23.9 IPS |
|
|
Face Detection (SP)
|
100% |
617
7.33 IPS |
|
|
Face Detection (HP)
|
100% |
1165
13.8 IPS |
|
|
Face Detection (Q)
|
96% |
991
11.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.89 IPS |
|
|
Depth Estimation (HP)
|
98% |
1605
12.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1219
11.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1833
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4026
5.18 IPS |
|
|
Style Transfer (Q)
|
98% |
4026
5.19 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
419
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
795
29.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
742
27.5 IPS |
|
|
Text Classification (SP)
|
35% |
9
83.3 IPS |
|
|
Text Classification (HP)
|
29% |
9
153.6 IPS |
|
|
Text Classification (Q)
|
32% |
12
158.7 IPS |
|
|
Machine Translation (SP)
|
100% |
261
4.50 IPS |
|
|
Machine Translation (HP)
|
100% |
325
5.60 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.72 IPS |
