samsung SM-A042M
Geekbench AI Score
94
Single Precision Score
89
Half Precision Score
100
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 09 2024 10:04 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A042M |
| Model ID | samsung SM-A042M |
| 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% |
54
10.1 IPS |
|
|
Image Classification (HP)
|
100% |
47
8.73 IPS |
|
|
Image Classification (Q)
|
100% |
71
13.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
71
1.15 IPS |
|
|
Image Segmentation (HP)
|
100% |
63
1.02 IPS |
|
|
Image Segmentation (Q)
|
98% |
116
1.88 IPS |
|
|
Pose Estimation (SP)
|
100% |
258
0.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
271
0.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
193
0.23 IPS |
|
|
Object Detection (SP)
|
100% |
53
4.18 IPS |
|
|
Object Detection (HP)
|
100% |
47
3.70 IPS |
|
|
Object Detection (Q)
|
83% |
65
5.23 IPS |
|
|
Face Detection (SP)
|
100% |
128
1.52 IPS |
|
|
Face Detection (HP)
|
100% |
125
1.48 IPS |
|
|
Face Detection (Q)
|
95% |
176
2.11 IPS |
|
|
Depth Estimation (SP)
|
100% |
143
1.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
136
1.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
141
1.29 IPS |
|
|
Style Transfer (SP)
|
89% |
487
0.63 IPS |
|
|
Style Transfer (HP)
|
89% |
474
0.61 IPS |
|
|
Style Transfer (Q)
|
98% |
469
0.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
72
2.65 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
71
2.61 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
98
3.62 IPS |
|
|
Text Classification (SP)
|
100% |
29
39.2 IPS |
|
|
Text Classification (HP)
|
100% |
24
32.4 IPS |
|
|
Text Classification (Q)
|
88% |
37
50.5 IPS |
|
|
Machine Translation (SP)
|
100% |
56
0.96 IPS |
|
|
Machine Translation (HP)
|
100% |
66
1.13 IPS |
|
|
Machine Translation (Q)
|
50% |
23
0.83 IPS |
