samsung SM-A037W
Geekbench AI Score
121
Single Precision Score
115
Half Precision Score
83
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 05:46 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-A037W |
| Model ID | samsung SM-A037W |
| Motherboard | a03su |
| 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 | 2.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
75
13.9 IPS |
|
|
Image Classification (HP)
|
100% |
76
14.1 IPS |
|
|
Image Classification (Q)
|
100% |
65
12.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
100
1.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
100
1.62 IPS |
|
|
Image Segmentation (Q)
|
98% |
86
1.41 IPS |
|
|
Pose Estimation (SP)
|
100% |
410
0.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
407
0.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
389
0.46 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.69 IPS |
|
|
Object Detection (HP)
|
100% |
73
5.80 IPS |
|
|
Object Detection (Q)
|
85% |
64
5.16 IPS |
|
|
Face Detection (SP)
|
100% |
213
2.53 IPS |
|
|
Face Detection (HP)
|
100% |
206
2.45 IPS |
|
|
Face Detection (Q)
|
97% |
166
1.97 IPS |
|
|
Depth Estimation (SP)
|
100% |
264
2.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
247
1.90 IPS |
|
|
Depth Estimation (Q)
|
64% |
196
1.79 IPS |
|
|
Style Transfer (SP)
|
100% |
750
0.96 IPS |
|
|
Style Transfer (HP)
|
100% |
731
0.94 IPS |
|
|
Style Transfer (Q)
|
98% |
680
0.88 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
149
5.52 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
146
5.38 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
130
4.80 IPS |
|
|
Text Classification (SP)
|
35% |
7
61.9 IPS |
|
|
Text Classification (HP)
|
35% |
6
62.1 IPS |
|
|
Text Classification (Q)
|
32% |
4
57.5 IPS |
|
|
Machine Translation (SP)
|
100% |
73
1.27 IPS |
|
|
Machine Translation (HP)
|
100% |
59
1.02 IPS |
|
|
Machine Translation (Q)
|
41% |
10
0.64 IPS |
