samsung SM-A042F
Geekbench AI Score
155
Single Precision Score
148
Half Precision Score
153
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 30 2025 04:39 PM |
| Views | 1 |
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% |
93
17.3 IPS |
|
|
Image Classification (HP)
|
100% |
74
13.8 IPS |
|
|
Image Classification (Q)
|
100% |
105
19.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
96
1.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
100
1.62 IPS |
|
|
Image Segmentation (Q)
|
98% |
183
2.97 IPS |
|
|
Pose Estimation (SP)
|
100% |
372
0.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
360
0.42 IPS |
|
|
Pose Estimation (Q)
|
84% |
250
0.30 IPS |
|
|
Object Detection (SP)
|
100% |
66
5.22 IPS |
|
|
Object Detection (HP)
|
100% |
75
5.95 IPS |
|
|
Object Detection (Q)
|
83% |
72
5.80 IPS |
|
|
Face Detection (SP)
|
100% |
169
2.01 IPS |
|
|
Face Detection (HP)
|
100% |
151
1.80 IPS |
|
|
Face Detection (Q)
|
95% |
257
3.07 IPS |
|
|
Depth Estimation (SP)
|
100% |
263
2.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
263
2.03 IPS |
|
|
Depth Estimation (Q)
|
64% |
247
2.26 IPS |
|
|
Style Transfer (SP)
|
89% |
673
0.87 IPS |
|
|
Style Transfer (HP)
|
89% |
666
0.86 IPS |
|
|
Style Transfer (Q)
|
98% |
625
0.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
129
4.77 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
115
4.25 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
138
5.12 IPS |
|
|
Text Classification (SP)
|
100% |
91
121.6 IPS |
|
|
Text Classification (HP)
|
100% |
78
104.6 IPS |
|
|
Text Classification (Q)
|
88% |
74
100.5 IPS |
|
|
Machine Translation (SP)
|
100% |
107
1.85 IPS |
|
|
Machine Translation (HP)
|
100% |
109
1.88 IPS |
|
|
Machine Translation (Q)
|
50% |
51
1.81 IPS |
