samsung SM-A166W
Geekbench AI Score
320
Single Precision Score
552
Half Precision Score
451
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 20 2025 02:08 AM |
| Views | 2 |
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% |
173
32.2 IPS |
|
|
Image Classification (HP)
|
100% |
326
60.6 IPS |
|
|
Image Classification (Q)
|
97% |
295
55.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
269
4.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
546
8.86 IPS |
|
|
Image Segmentation (Q)
|
98% |
534
8.69 IPS |
|
|
Pose Estimation (SP)
|
100% |
1129
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
2118
2.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
2082
2.44 IPS |
|
|
Object Detection (SP)
|
100% |
175
13.9 IPS |
|
|
Object Detection (HP)
|
99% |
375
29.8 IPS |
|
|
Object Detection (Q)
|
83% |
302
24.4 IPS |
|
|
Face Detection (SP)
|
100% |
635
7.55 IPS |
|
|
Face Detection (HP)
|
100% |
1193
14.2 IPS |
|
|
Face Detection (Q)
|
96% |
1006
12.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.94 IPS |
|
|
Depth Estimation (HP)
|
98% |
1475
11.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
1159
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1836
2.36 IPS |
|
|
Style Transfer (HP)
|
100% |
4031
5.18 IPS |
|
|
Style Transfer (Q)
|
98% |
4003
5.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
428
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
779
28.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
754
27.9 IPS |
|
|
Text Classification (SP)
|
35% |
11
101.6 IPS |
|
|
Text Classification (HP)
|
29% |
10
165.1 IPS |
|
|
Text Classification (Q)
|
32% |
12
157.8 IPS |
|
|
Machine Translation (SP)
|
100% |
294
5.07 IPS |
|
|
Machine Translation (HP)
|
100% |
339
5.84 IPS |
|
|
Machine Translation (Q)
|
43% |
85
4.95 IPS |
