samsung SM-A057M
Geekbench ML Score
74
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 05:49 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A057M |
| Model ID | samsung SM-A057M |
| Motherboard | bengal |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.46 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
32
5.98 IPS |
|
|
Image Classification (F16)
|
100% |
65
12.2 IPS |
|
|
Image Classification (I8)
|
97% |
67
12.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
30
0.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
98
1.64 IPS |
|
|
Image Segmentation (I8)
|
98% |
100
1.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
54
0.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
106
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
105
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
32
2.42 IPS |
|
|
Object Detection (F16)
|
100% |
53
3.92 IPS |
|
|
Object Detection (I8)
|
62% |
52
3.88 IPS |
|
|
Face Detection (F32)
|
100% |
80
0.95 IPS |
|
|
Face Detection (F16)
|
97% |
202
2.40 IPS |
|
|
Face Detection (I8)
|
87% |
208
2.47 IPS |
|
|
Depth Estimation (F32)
|
100% |
75
0.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
153
1.19 IPS |
|
|
Depth Estimation (I8)
|
95% |
154
1.19 IPS |
|
|
Style Transfer (F32)
|
0
|
||
|
Style Transfer (F16)
|
100% |
281
0.37 IPS |
|
|
Style Transfer (I8)
|
98% |
280
0.37 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
37
1.33 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
76
2.73 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
76
2.73 IPS |
|
|
Text Classification (F32)
|
100% |
66
94.3 IPS |
|
|
Text Classification (F16)
|
100% |
66
94.5 IPS |
|
|
Text Classification (I8)
|
92% |
86
123.6 IPS |
|
|
Machine Translation (F32)
|
100% |
122
2.25 IPS |
|
|
Machine Translation (F16)
|
100% |
123
2.27 IPS |
|
|
Machine Translation (I8)
|
64% |
127
2.33 IPS |
