samsung SM-A042F
Geekbench AI Score
184
Single Precision Score
190
Half Precision Score
203
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 05 2024 07:25 AM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CB |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A042F |
| Model ID | samsung SM-A042F |
| Motherboard | a04e |
| 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 | 2.71 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
86
16.1 IPS |
|
|
Image Classification (HP)
|
100% |
84
15.7 IPS |
|
|
Image Classification (Q)
|
100% |
123
22.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
94
1.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
89
1.44 IPS |
|
|
Image Segmentation (Q)
|
98% |
171
2.78 IPS |
|
|
Pose Estimation (SP)
|
100% |
448
0.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
449
0.52 IPS |
|
|
Pose Estimation (Q)
|
84% |
314
0.37 IPS |
|
|
Object Detection (SP)
|
100% |
92
7.26 IPS |
|
|
Object Detection (HP)
|
100% |
103
8.17 IPS |
|
|
Object Detection (Q)
|
83% |
131
10.6 IPS |
|
|
Face Detection (SP)
|
100% |
240
2.85 IPS |
|
|
Face Detection (HP)
|
100% |
263
3.13 IPS |
|
|
Face Detection (Q)
|
95% |
379
4.52 IPS |
|
|
Depth Estimation (SP)
|
100% |
331
2.55 IPS |
|
|
Depth Estimation (HP)
|
99% |
330
2.54 IPS |
|
|
Depth Estimation (Q)
|
64% |
324
2.96 IPS |
|
|
Style Transfer (SP)
|
89% |
811
1.05 IPS |
|
|
Style Transfer (HP)
|
89% |
853
1.11 IPS |
|
|
Style Transfer (Q)
|
98% |
797
1.03 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
158
5.84 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
169
6.25 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
192
7.12 IPS |
|
|
Text Classification (SP)
|
100% |
100
133.9 IPS |
|
|
Text Classification (HP)
|
100% |
107
142.6 IPS |
|
|
Text Classification (Q)
|
88% |
121
163.9 IPS |
|
|
Machine Translation (SP)
|
100% |
135
2.33 IPS |
|
|
Machine Translation (HP)
|
100% |
136
2.34 IPS |
|
|
Machine Translation (Q)
|
50% |
63
2.23 IPS |
