samsung SM-A042F
Geekbench AI Score
151
Single Precision Score
141
Half Precision Score
170
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | March 20 2025 08:51 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A042F |
| Model ID | samsung SM-A042F |
| Motherboard | a04e |
| 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 | 2.71 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
106
19.8 IPS |
|
|
Image Classification (HP)
|
100% |
65
12.1 IPS |
|
|
Image Classification (Q)
|
100% |
110
20.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
98
1.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
99
1.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
210
3.42 IPS |
|
|
Pose Estimation (SP)
|
100% |
393
0.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
372
0.43 IPS |
|
|
Pose Estimation (Q)
|
84% |
292
0.35 IPS |
|
|
Object Detection (SP)
|
100% |
77
6.13 IPS |
|
|
Object Detection (HP)
|
100% |
72
5.70 IPS |
|
|
Object Detection (Q)
|
83% |
113
9.15 IPS |
|
|
Face Detection (SP)
|
100% |
213
2.53 IPS |
|
|
Face Detection (HP)
|
100% |
186
2.21 IPS |
|
|
Face Detection (Q)
|
95% |
358
4.27 IPS |
|
|
Depth Estimation (SP)
|
100% |
220
1.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
241
1.86 IPS |
|
|
Depth Estimation (Q)
|
64% |
245
2.24 IPS |
|
|
Style Transfer (SP)
|
89% |
687
0.89 IPS |
|
|
Style Transfer (HP)
|
89% |
601
0.78 IPS |
|
|
Style Transfer (Q)
|
98% |
663
0.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
98
3.63 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
131
4.82 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
130
4.80 IPS |
|
|
Text Classification (SP)
|
100% |
67
89.6 IPS |
|
|
Text Classification (HP)
|
100% |
60
79.8 IPS |
|
|
Text Classification (Q)
|
88% |
91
123.0 IPS |
|
|
Machine Translation (SP)
|
100% |
96
1.66 IPS |
|
|
Machine Translation (HP)
|
100% |
88
1.52 IPS |
|
|
Machine Translation (Q)
|
50% |
39
1.40 IPS |
