samsung SM-A037M
Geekbench ML Score
163
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 01:55 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
95
17.7 IPS |
|
|
Image Classification (F16)
|
100% |
90
16.8 IPS |
|
|
Image Classification (I8)
|
97% |
146
27.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
130
2.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
130
2.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
167
2.79 IPS |
|
|
Pose Estimation (F32)
|
100% |
126
0.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
129
0.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
442
0.54 IPS |
|
|
Object Detection (F32)
|
100% |
94
7.02 IPS |
|
|
Object Detection (F16)
|
100% |
89
6.66 IPS |
|
|
Object Detection (I8)
|
61% |
168
12.6 IPS |
|
|
Face Detection (F32)
|
100% |
189
2.24 IPS |
|
|
Face Detection (F16)
|
100% |
190
2.26 IPS |
|
|
Face Detection (I8)
|
86% |
370
4.40 IPS |
|
|
Depth Estimation (F32)
|
100% |
167
1.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
158
1.23 IPS |
|
|
Depth Estimation (I8)
|
95% |
350
2.72 IPS |
|
|
Style Transfer (F32)
|
100% |
205
0.27 IPS |
|
|
Style Transfer (F16)
|
100% |
233
0.31 IPS |
|
|
Style Transfer (I8)
|
98% |
695
0.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
115
4.09 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
112
4.01 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
255
9.12 IPS |
|
|
Text Classification (F32)
|
100% |
110
158.4 IPS |
|
|
Text Classification (F16)
|
100% |
110
158.5 IPS |
|
|
Text Classification (I8)
|
92% |
121
173.5 IPS |
|
|
Machine Translation (F32)
|
100% |
167
3.08 IPS |
|
|
Machine Translation (F16)
|
100% |
169
3.11 IPS |
|
|
Machine Translation (I8)
|
64% |
121
2.22 IPS |
