samsung SM-A166W
Geekbench AI Score
313
Single Precision Score
548
Half Precision Score
463
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 25 2025 02:42 AM |
| Views | 8 |
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% |
166
30.9 IPS |
|
|
Image Classification (HP)
|
100% |
335
62.2 IPS |
|
|
Image Classification (Q)
|
97% |
313
58.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
555
9.00 IPS |
|
|
Image Segmentation (Q)
|
98% |
531
8.63 IPS |
|
|
Pose Estimation (SP)
|
100% |
1131
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2124
2.48 IPS |
|
|
Pose Estimation (Q)
|
95% |
2088
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
326
25.8 IPS |
|
|
Object Detection (Q)
|
83% |
305
24.7 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
1184
14.1 IPS |
|
|
Face Detection (Q)
|
96% |
1021
12.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.93 IPS |
|
|
Depth Estimation (HP)
|
98% |
1488
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1184
11.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1832
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4002
5.14 IPS |
|
|
Style Transfer (Q)
|
98% |
3974
5.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
418
15.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
783
28.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
833
30.9 IPS |
|
|
Text Classification (SP)
|
35% |
11
98.6 IPS |
|
|
Text Classification (HP)
|
29% |
10
164.3 IPS |
|
|
Text Classification (Q)
|
32% |
13
164.6 IPS |
|
|
Machine Translation (SP)
|
100% |
261
4.49 IPS |
|
|
Machine Translation (HP)
|
100% |
347
5.97 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.82 IPS |
