samsung SM-A037M
Geekbench ML Score
23
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 02:21 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-A037M |
| Model ID | samsung SM-A037M |
| Motherboard | a03s |
| CPU Information | |
|---|---|
| Name | ARM MT6765V/WB |
| 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 | 3.69 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
24
4.47 IPS |
|
|
Image Classification (F16)
|
100% |
36
6.66 IPS |
|
|
Image Classification (I8)
|
99% |
34
6.40 IPS |
|
|
Image Segmentation (F32)
|
100% |
34
0.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
43
0.72 IPS |
|
|
Image Segmentation (I8)
|
98% |
43
0.71 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
0
|
||
|
Object Detection (F32)
|
100% |
18
1.35 IPS |
|
|
Object Detection (F16)
|
100% |
26
1.92 IPS |
|
|
Object Detection (I8)
|
55% |
25
1.88 IPS |
|
|
Face Detection (F32)
|
100% |
72
0.85 IPS |
|
|
Face Detection (F16)
|
98% |
97
1.15 IPS |
|
|
Face Detection (I8)
|
86% |
91
1.08 IPS |
|
|
Depth Estimation (F32)
|
100% |
47
0.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
74
0.57 IPS |
|
|
Depth Estimation (I8)
|
93% |
71
0.55 IPS |
|
|
Style Transfer (F32)
|
0
|
||
|
Style Transfer (F16)
|
100% |
157
0.21 IPS |
|
|
Style Transfer (I8)
|
0
|
||
|
Image Super-Resolution (F32)
|
100% |
21
0.77 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
36
1.29 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
33
1.19 IPS |
|
|
Text Classification (F32)
|
100% |
31
45.3 IPS |
|
|
Text Classification (F16)
|
100% |
32
46.3 IPS |
|
|
Text Classification (I8)
|
92% |
47
67.5 IPS |
|
|
Machine Translation (F32)
|
100% |
60
1.10 IPS |
|
|
Machine Translation (F16)
|
100% |
58
1.06 IPS |
|
|
Machine Translation (I8)
|
64% |
69
1.27 IPS |
