samsung SM-A125N
Geekbench AI Score
143
Single Precision Score
140
Half Precision Score
151
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 01 2025 11:39 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-A125N |
| Model ID | samsung SM-A125N |
| Motherboard | a12 |
| CPU Information | |
|---|---|
| Name | ARM MT6765V/CB |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 2.68 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
60
11.1 IPS |
|
|
Image Classification (HP)
|
100% |
55
10.2 IPS |
|
|
Image Classification (Q)
|
100% |
82
15.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
88
1.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
90
1.45 IPS |
|
|
Image Segmentation (Q)
|
98% |
157
2.54 IPS |
|
|
Pose Estimation (SP)
|
100% |
445
0.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
426
0.50 IPS |
|
|
Pose Estimation (Q)
|
84% |
345
0.41 IPS |
|
|
Object Detection (SP)
|
100% |
82
6.47 IPS |
|
|
Object Detection (HP)
|
100% |
83
6.55 IPS |
|
|
Object Detection (Q)
|
83% |
91
7.33 IPS |
|
|
Face Detection (SP)
|
100% |
215
2.56 IPS |
|
|
Face Detection (HP)
|
100% |
197
2.34 IPS |
|
|
Face Detection (Q)
|
95% |
292
3.49 IPS |
|
|
Depth Estimation (SP)
|
100% |
274
2.11 IPS |
|
|
Depth Estimation (HP)
|
99% |
256
1.97 IPS |
|
|
Depth Estimation (Q)
|
64% |
248
2.27 IPS |
|
|
Style Transfer (SP)
|
89% |
861
1.12 IPS |
|
|
Style Transfer (HP)
|
89% |
836
1.09 IPS |
|
|
Style Transfer (Q)
|
98% |
843
1.09 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
127
4.68 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
128
4.73 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
135
5.00 IPS |
|
|
Text Classification (SP)
|
100% |
37
50.0 IPS |
|
|
Text Classification (HP)
|
100% |
38
50.1 IPS |
|
|
Text Classification (Q)
|
88% |
50
67.9 IPS |
|
|
Machine Translation (SP)
|
100% |
83
1.42 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.49 IPS |
|
|
Machine Translation (Q)
|
50% |
39
1.40 IPS |
