samsung SM-A042F
Geekbench AI Score
126
Single Precision Score
116
Half Precision Score
83
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 15 2025 04:47 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
74
13.8 IPS |
|
|
Image Classification (HP)
|
100% |
76
14.1 IPS |
|
|
Image Classification (Q)
|
100% |
65
12.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
102
1.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
99
1.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
87
1.42 IPS |
|
|
Pose Estimation (SP)
|
100% |
418
0.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
413
0.48 IPS |
|
|
Pose Estimation (Q)
|
96% |
397
0.47 IPS |
|
|
Object Detection (SP)
|
100% |
76
6.03 IPS |
|
|
Object Detection (HP)
|
100% |
73
5.78 IPS |
|
|
Object Detection (Q)
|
85% |
64
5.12 IPS |
|
|
Face Detection (SP)
|
100% |
214
2.54 IPS |
|
|
Face Detection (HP)
|
100% |
206
2.45 IPS |
|
|
Face Detection (Q)
|
97% |
165
1.97 IPS |
|
|
Depth Estimation (SP)
|
100% |
256
1.98 IPS |
|
|
Depth Estimation (HP)
|
99% |
245
1.89 IPS |
|
|
Depth Estimation (Q)
|
64% |
196
1.79 IPS |
|
|
Style Transfer (SP)
|
100% |
754
0.97 IPS |
|
|
Style Transfer (HP)
|
100% |
756
0.97 IPS |
|
|
Style Transfer (Q)
|
98% |
712
0.92 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
154
5.68 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
148
5.47 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
134
4.97 IPS |
|
|
Text Classification (SP)
|
35% |
7
60.9 IPS |
|
|
Text Classification (HP)
|
35% |
6
62.5 IPS |
|
|
Text Classification (Q)
|
32% |
4
56.5 IPS |
|
|
Machine Translation (SP)
|
100% |
95
1.63 IPS |
|
|
Machine Translation (HP)
|
100% |
60
1.03 IPS |
|
|
Machine Translation (Q)
|
41% |
9
0.62 IPS |
