samsung SM-A037M
Geekbench ML Score
159
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 03:14 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% |
88
16.4 IPS |
|
|
Image Classification (F16)
|
100% |
88
16.5 IPS |
|
|
Image Classification (I8)
|
97% |
145
27.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
130
2.18 IPS |
|
|
Image Segmentation (F16)
|
100% |
129
2.15 IPS |
|
|
Image Segmentation (I8)
|
98% |
166
2.77 IPS |
|
|
Pose Estimation (F32)
|
100% |
123
0.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
119
0.14 IPS |
|
|
Pose Estimation (I8)
|
100% |
423
0.51 IPS |
|
|
Object Detection (F32)
|
100% |
89
6.61 IPS |
|
|
Object Detection (F16)
|
100% |
84
6.25 IPS |
|
|
Object Detection (I8)
|
61% |
171
12.8 IPS |
|
|
Face Detection (F32)
|
100% |
185
2.21 IPS |
|
|
Face Detection (F16)
|
100% |
183
2.18 IPS |
|
|
Face Detection (I8)
|
86% |
355
4.22 IPS |
|
|
Depth Estimation (F32)
|
100% |
157
1.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
155
1.20 IPS |
|
|
Depth Estimation (I8)
|
95% |
336
2.60 IPS |
|
|
Style Transfer (F32)
|
100% |
231
0.30 IPS |
|
|
Style Transfer (F16)
|
100% |
233
0.31 IPS |
|
|
Style Transfer (I8)
|
98% |
696
0.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
114
4.06 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
109
3.88 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
242
8.63 IPS |
|
|
Text Classification (F32)
|
100% |
103
147.8 IPS |
|
|
Text Classification (F16)
|
100% |
101
145.5 IPS |
|
|
Text Classification (I8)
|
92% |
116
166.1 IPS |
|
|
Machine Translation (F32)
|
100% |
166
3.05 IPS |
|
|
Machine Translation (F16)
|
100% |
164
3.02 IPS |
|
|
Machine Translation (I8)
|
64% |
123
2.26 IPS |
