samsung SM-A166W
Geekbench AI Score
315
Single Precision Score
533
Half Precision Score
454
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 07 2025 03:27 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
173
32.1 IPS |
|
|
Image Classification (HP)
|
100% |
333
62.0 IPS |
|
|
Image Classification (Q)
|
97% |
305
57.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
270
4.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
542
8.79 IPS |
|
|
Image Segmentation (Q)
|
98% |
528
8.58 IPS |
|
|
Pose Estimation (SP)
|
100% |
1131
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2091
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
309
24.5 IPS |
|
|
Object Detection (Q)
|
83% |
293
23.6 IPS |
|
|
Face Detection (SP)
|
100% |
630
7.48 IPS |
|
|
Face Detection (HP)
|
100% |
1171
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1003
12.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.93 IPS |
|
|
Depth Estimation (HP)
|
98% |
1483
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1140
10.8 IPS |
|
|
Style Transfer (SP)
|
100% |
1846
2.37 IPS |
|
|
Style Transfer (HP)
|
100% |
4007
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3984
5.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
411
15.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
755
27.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
800
29.7 IPS |
|
|
Text Classification (SP)
|
35% |
11
98.5 IPS |
|
|
Text Classification (HP)
|
29% |
9
150.5 IPS |
|
|
Text Classification (Q)
|
32% |
13
162.6 IPS |
|
|
Machine Translation (SP)
|
100% |
262
4.51 IPS |
|
|
Machine Translation (HP)
|
100% |
334
5.75 IPS |
|
|
Machine Translation (Q)
|
43% |
81
4.69 IPS |
