samsung SM-A042M
Geekbench AI Score
137
Single Precision Score
135
Half Precision Score
153
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 28 2024 12:35 AM |
| Views | 6 |
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% |
64
11.9 IPS |
|
|
Image Classification (HP)
|
100% |
57
10.7 IPS |
|
|
Image Classification (Q)
|
100% |
90
16.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
82
1.33 IPS |
|
|
Image Segmentation (HP)
|
100% |
82
1.33 IPS |
|
|
Image Segmentation (Q)
|
98% |
148
2.41 IPS |
|
|
Pose Estimation (SP)
|
100% |
299
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
335
0.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
224
0.27 IPS |
|
|
Object Detection (SP)
|
100% |
70
5.58 IPS |
|
|
Object Detection (HP)
|
100% |
68
5.37 IPS |
|
|
Object Detection (Q)
|
87% |
102
8.19 IPS |
|
|
Face Detection (SP)
|
100% |
186
2.21 IPS |
|
|
Face Detection (HP)
|
100% |
181
2.16 IPS |
|
|
Face Detection (Q)
|
95% |
296
3.54 IPS |
|
|
Depth Estimation (SP)
|
100% |
258
1.99 IPS |
|
|
Depth Estimation (HP)
|
100% |
248
1.91 IPS |
|
|
Depth Estimation (Q)
|
75% |
277
2.25 IPS |
|
|
Style Transfer (SP)
|
89% |
609
0.79 IPS |
|
|
Style Transfer (HP)
|
89% |
613
0.80 IPS |
|
|
Style Transfer (Q)
|
98% |
576
0.74 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
112
4.12 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
110
4.05 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
128
4.76 IPS |
|
|
Text Classification (SP)
|
100% |
71
94.9 IPS |
|
|
Text Classification (HP)
|
100% |
64
85.5 IPS |
|
|
Text Classification (Q)
|
88% |
78
105.0 IPS |
|
|
Machine Translation (SP)
|
100% |
95
1.64 IPS |
|
|
Machine Translation (HP)
|
100% |
100
1.73 IPS |
|
|
Machine Translation (Q)
|
50% |
51
1.80 IPS |
