samsung SM-A042M
Geekbench AI Score
105
Single Precision Score
97
Half Precision Score
115
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 29 2024 02:39 AM |
| Views | 12 |
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% |
71
13.2 IPS |
|
|
Image Classification (HP)
|
100% |
59
10.9 IPS |
|
|
Image Classification (Q)
|
100% |
94
17.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
84
1.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
75
1.22 IPS |
|
|
Image Segmentation (Q)
|
98% |
136
2.21 IPS |
|
|
Pose Estimation (SP)
|
100% |
313
0.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
263
0.31 IPS |
|
|
Pose Estimation (Q)
|
84% |
200
0.24 IPS |
|
|
Object Detection (SP)
|
100% |
51
4.03 IPS |
|
|
Object Detection (HP)
|
100% |
52
4.12 IPS |
|
|
Object Detection (Q)
|
83% |
73
5.92 IPS |
|
|
Face Detection (SP)
|
100% |
126
1.50 IPS |
|
|
Face Detection (HP)
|
100% |
134
1.60 IPS |
|
|
Face Detection (Q)
|
95% |
225
2.69 IPS |
|
|
Depth Estimation (SP)
|
100% |
133
1.02 IPS |
|
|
Depth Estimation (HP)
|
99% |
175
1.35 IPS |
|
|
Depth Estimation (Q)
|
64% |
164
1.51 IPS |
|
|
Style Transfer (SP)
|
89% |
472
0.61 IPS |
|
|
Style Transfer (HP)
|
89% |
470
0.61 IPS |
|
|
Style Transfer (Q)
|
98% |
470
0.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
77
2.83 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
73
2.69 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
86
3.20 IPS |
|
|
Text Classification (SP)
|
100% |
46
61.5 IPS |
|
|
Text Classification (HP)
|
100% |
26
34.4 IPS |
|
|
Text Classification (Q)
|
88% |
47
63.5 IPS |
|
|
Machine Translation (SP)
|
100% |
65
1.11 IPS |
|
|
Machine Translation (HP)
|
100% |
61
1.04 IPS |
|
|
Machine Translation (Q)
|
50% |
31
1.09 IPS |
