samsung SM-A042F
Geekbench AI Score
159
Single Precision Score
149
Half Precision Score
158
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 28 2025 03:56 AM |
| Views | 3 |
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% |
113
21.0 IPS |
|
|
Image Classification (HP)
|
100% |
74
13.7 IPS |
|
|
Image Classification (Q)
|
100% |
109
20.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
99
1.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
95
1.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
148
2.40 IPS |
|
|
Pose Estimation (SP)
|
100% |
401
0.47 IPS |
|
|
Pose Estimation (HP)
|
100% |
416
0.49 IPS |
|
|
Pose Estimation (Q)
|
84% |
245
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
78
6.18 IPS |
|
|
Object Detection (HP)
|
100% |
76
6.06 IPS |
|
|
Object Detection (Q)
|
83% |
104
8.42 IPS |
|
|
Face Detection (SP)
|
100% |
198
2.35 IPS |
|
|
Face Detection (HP)
|
100% |
194
2.30 IPS |
|
|
Face Detection (Q)
|
95% |
287
3.43 IPS |
|
|
Depth Estimation (SP)
|
100% |
256
1.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
248
1.91 IPS |
|
|
Depth Estimation (Q)
|
64% |
246
2.26 IPS |
|
|
Style Transfer (SP)
|
89% |
686
0.89 IPS |
|
|
Style Transfer (HP)
|
89% |
676
0.88 IPS |
|
|
Style Transfer (Q)
|
98% |
625
0.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
110
4.07 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
110
4.06 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
137
5.09 IPS |
|
|
Text Classification (SP)
|
100% |
73
97.4 IPS |
|
|
Text Classification (HP)
|
100% |
71
94.9 IPS |
|
|
Text Classification (Q)
|
88% |
79
106.1 IPS |
|
|
Machine Translation (SP)
|
100% |
112
1.94 IPS |
|
|
Machine Translation (HP)
|
100% |
101
1.73 IPS |
|
|
Machine Translation (Q)
|
50% |
50
1.78 IPS |
