samsung SM-A042M
Geekbench AI Score
73
Single Precision Score
65
Half Precision Score
77
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 15 2024 05:52 AM |
| Views | 14 |
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% |
33
6.10 IPS |
|
|
Image Classification (HP)
|
100% |
30
5.49 IPS |
|
|
Image Classification (Q)
|
100% |
44
8.20 IPS |
|
|
Image Segmentation (SP)
|
100% |
58
0.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
57
0.92 IPS |
|
|
Image Segmentation (Q)
|
98% |
102
1.66 IPS |
|
|
Pose Estimation (SP)
|
100% |
236
0.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
241
0.28 IPS |
|
|
Pose Estimation (Q)
|
84% |
186
0.22 IPS |
|
|
Object Detection (SP)
|
100% |
32
2.57 IPS |
|
|
Object Detection (HP)
|
100% |
35
2.75 IPS |
|
|
Object Detection (Q)
|
83% |
42
3.37 IPS |
|
|
Face Detection (SP)
|
100% |
94
1.12 IPS |
|
|
Face Detection (HP)
|
100% |
94
1.11 IPS |
|
|
Face Detection (Q)
|
95% |
168
2.01 IPS |
|
|
Depth Estimation (SP)
|
100% |
112
0.86 IPS |
|
|
Depth Estimation (HP)
|
99% |
101
0.78 IPS |
|
|
Depth Estimation (Q)
|
64% |
118
1.08 IPS |
|
|
Style Transfer (SP)
|
89% |
460
0.60 IPS |
|
|
Style Transfer (HP)
|
89% |
483
0.63 IPS |
|
|
Style Transfer (Q)
|
98% |
433
0.56 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
58
2.14 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
56
2.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
73
2.69 IPS |
|
|
Text Classification (SP)
|
100% |
36
48.3 IPS |
|
|
Text Classification (HP)
|
100% |
14
18.3 IPS |
|
|
Text Classification (Q)
|
88% |
24
32.5 IPS |
|
|
Machine Translation (SP)
|
100% |
30
0.51 IPS |
|
|
Machine Translation (HP)
|
100% |
29
0.49 IPS |
|
|
Machine Translation (Q)
|
50% |
15
0.53 IPS |
