samsung SM-A042F
Geekbench AI Score
143
Single Precision Score
162
Half Precision Score
168
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | October 17 2024 02:48 PM |
| Views | 5 |
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% |
19
3.44 IPS |
|
|
Image Classification (HP)
|
100% |
70
13.0 IPS |
|
|
Image Classification (Q)
|
100% |
96
17.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
94
1.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
101
1.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
168
2.73 IPS |
|
|
Pose Estimation (SP)
|
100% |
406
0.47 IPS |
|
|
Pose Estimation (HP)
|
100% |
397
0.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
281
0.33 IPS |
|
|
Object Detection (SP)
|
100% |
83
6.57 IPS |
|
|
Object Detection (HP)
|
100% |
86
6.84 IPS |
|
|
Object Detection (Q)
|
83% |
111
8.99 IPS |
|
|
Face Detection (SP)
|
100% |
217
2.58 IPS |
|
|
Face Detection (HP)
|
100% |
216
2.56 IPS |
|
|
Face Detection (Q)
|
95% |
302
3.60 IPS |
|
|
Depth Estimation (SP)
|
100% |
284
2.19 IPS |
|
|
Depth Estimation (HP)
|
99% |
246
1.89 IPS |
|
|
Depth Estimation (Q)
|
64% |
258
2.36 IPS |
|
|
Style Transfer (SP)
|
89% |
724
0.94 IPS |
|
|
Style Transfer (HP)
|
89% |
751
0.97 IPS |
|
|
Style Transfer (Q)
|
98% |
705
0.91 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
134
4.96 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
133
4.90 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
155
5.75 IPS |
|
|
Text Classification (SP)
|
100% |
83
110.7 IPS |
|
|
Text Classification (HP)
|
100% |
83
110.5 IPS |
|
|
Text Classification (Q)
|
88% |
83
111.4 IPS |
|
|
Machine Translation (SP)
|
100% |
123
2.11 IPS |
|
|
Machine Translation (HP)
|
100% |
121
2.08 IPS |
|
|
Machine Translation (Q)
|
50% |
53
1.90 IPS |
