samsung SM-A042F
Geekbench AI Score
172
Single Precision Score
180
Half Precision Score
185
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 06 2025 10:38 AM |
| Views | 2 |
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% |
65
12.1 IPS |
|
|
Image Classification (HP)
|
100% |
80
14.9 IPS |
|
|
Image Classification (Q)
|
100% |
94
17.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
84
1.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
87
1.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
134
2.18 IPS |
|
|
Pose Estimation (SP)
|
100% |
429
0.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
456
0.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
304
0.36 IPS |
|
|
Object Detection (SP)
|
100% |
90
7.16 IPS |
|
|
Object Detection (HP)
|
100% |
89
7.10 IPS |
|
|
Object Detection (Q)
|
83% |
133
10.7 IPS |
|
|
Face Detection (SP)
|
100% |
234
2.78 IPS |
|
|
Face Detection (HP)
|
100% |
244
2.90 IPS |
|
|
Face Detection (Q)
|
95% |
363
4.33 IPS |
|
|
Depth Estimation (SP)
|
100% |
289
2.23 IPS |
|
|
Depth Estimation (HP)
|
99% |
318
2.45 IPS |
|
|
Depth Estimation (Q)
|
64% |
302
2.77 IPS |
|
|
Style Transfer (SP)
|
89% |
774
1.00 IPS |
|
|
Style Transfer (HP)
|
89% |
801
1.04 IPS |
|
|
Style Transfer (Q)
|
98% |
742
0.96 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
161
5.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
149
5.49 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
172
6.37 IPS |
|
|
Text Classification (SP)
|
100% |
104
139.5 IPS |
|
|
Text Classification (HP)
|
100% |
107
142.4 IPS |
|
|
Text Classification (Q)
|
88% |
109
146.7 IPS |
|
|
Machine Translation (SP)
|
100% |
127
2.18 IPS |
|
|
Machine Translation (HP)
|
100% |
128
2.20 IPS |
|
|
Machine Translation (Q)
|
50% |
61
2.16 IPS |
