samsung SM-A166W
Geekbench AI Score
306
Single Precision Score
540
Half Precision Score
476
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | November 27 2025 03:48 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% |
166
30.9 IPS |
|
|
Image Classification (HP)
|
100% |
336
62.4 IPS |
|
|
Image Classification (Q)
|
97% |
408
76.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
271
4.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
556
9.02 IPS |
|
|
Image Segmentation (Q)
|
98% |
546
8.87 IPS |
|
|
Pose Estimation (SP)
|
100% |
1131
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2088
2.45 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
323
25.6 IPS |
|
|
Object Detection (Q)
|
83% |
294
23.7 IPS |
|
|
Face Detection (SP)
|
100% |
597
7.10 IPS |
|
|
Face Detection (HP)
|
100% |
1168
13.9 IPS |
|
|
Face Detection (Q)
|
96% |
1115
13.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
773
5.95 IPS |
|
|
Depth Estimation (HP)
|
98% |
1491
11.5 IPS |
|
|
Depth Estimation (Q)
|
62% |
1156
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1836
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4004
5.15 IPS |
|
|
Style Transfer (Q)
|
98% |
3977
5.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
411
15.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
802
29.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
731
27.1 IPS |
|
|
Text Classification (SP)
|
35% |
9
83.5 IPS |
|
|
Text Classification (HP)
|
29% |
9
155.6 IPS |
|
|
Text Classification (Q)
|
32% |
13
164.4 IPS |
|
|
Machine Translation (SP)
|
100% |
265
4.56 IPS |
|
|
Machine Translation (HP)
|
100% |
333
5.74 IPS |
|
|
Machine Translation (Q)
|
43% |
90
5.22 IPS |
