samsung SM-A042F
Geekbench AI Score
148
Single Precision Score
150
Half Precision Score
162
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | December 01 2024 02:27 AM |
| Views | 9 |
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% |
52
9.58 IPS |
|
|
Image Classification (HP)
|
100% |
57
10.6 IPS |
|
|
Image Classification (Q)
|
100% |
77
14.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
83
1.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
72
1.17 IPS |
|
|
Image Segmentation (Q)
|
98% |
160
2.60 IPS |
|
|
Pose Estimation (SP)
|
100% |
347
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
397
0.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
276
0.33 IPS |
|
|
Object Detection (SP)
|
100% |
78
6.20 IPS |
|
|
Object Detection (HP)
|
100% |
83
6.60 IPS |
|
|
Object Detection (Q)
|
83% |
112
9.08 IPS |
|
|
Face Detection (SP)
|
100% |
209
2.49 IPS |
|
|
Face Detection (HP)
|
100% |
200
2.37 IPS |
|
|
Face Detection (Q)
|
95% |
298
3.55 IPS |
|
|
Depth Estimation (SP)
|
100% |
278
2.15 IPS |
|
|
Depth Estimation (HP)
|
99% |
263
2.03 IPS |
|
|
Depth Estimation (Q)
|
64% |
255
2.34 IPS |
|
|
Style Transfer (SP)
|
89% |
711
0.92 IPS |
|
|
Style Transfer (HP)
|
89% |
726
0.94 IPS |
|
|
Style Transfer (Q)
|
98% |
686
0.88 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
122
4.51 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
132
4.87 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
151
5.59 IPS |
|
|
Text Classification (SP)
|
100% |
73
97.2 IPS |
|
|
Text Classification (HP)
|
100% |
75
99.6 IPS |
|
|
Text Classification (Q)
|
88% |
90
120.9 IPS |
|
|
Machine Translation (SP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (HP)
|
100% |
115
1.98 IPS |
|
|
Machine Translation (Q)
|
50% |
49
1.74 IPS |
