Samsung Galaxy F62
Geekbench AI Score
180
Single Precision Score
263
Half Precision Score
189
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 25 2024 10:29 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Samsung Exynos 9825 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy F62 |
| Model ID | samsung SM-E625F |
| Motherboard | exynos9825 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
158
29.4 IPS |
|
|
Image Classification (HP)
|
100% |
157
29.2 IPS |
|
|
Image Classification (Q)
|
97% |
337
62.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
223
3.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
206
3.34 IPS |
|
|
Image Segmentation (Q)
|
98% |
88
1.44 IPS |
|
|
Pose Estimation (SP)
|
100% |
574
0.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
2503
2.92 IPS |
|
|
Pose Estimation (Q)
|
98% |
501
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
87
6.90 IPS |
|
|
Object Detection (HP)
|
100% |
86
6.80 IPS |
|
|
Object Detection (Q)
|
89% |
77
6.19 IPS |
|
|
Face Detection (SP)
|
100% |
211
2.50 IPS |
|
|
Face Detection (HP)
|
100% |
102
1.21 IPS |
|
|
Face Detection (Q)
|
97% |
192
2.29 IPS |
|
|
Depth Estimation (SP)
|
100% |
94
0.72 IPS |
|
|
Depth Estimation (HP)
|
100% |
188
1.45 IPS |
|
|
Depth Estimation (Q)
|
73% |
166
1.35 IPS |
|
|
Style Transfer (SP)
|
100% |
244
0.31 IPS |
|
|
Style Transfer (HP)
|
100% |
187
0.24 IPS |
|
|
Style Transfer (Q)
|
98% |
401
0.52 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
389
14.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
750
27.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
562
20.8 IPS |
|
|
Text Classification (SP)
|
100% |
28
37.2 IPS |
|
|
Text Classification (HP)
|
100% |
232
309.0 IPS |
|
|
Text Classification (Q)
|
91% |
25
33.4 IPS |
|
|
Machine Translation (SP)
|
100% |
385
6.64 IPS |
|
|
Machine Translation (HP)
|
100% |
367
6.32 IPS |
|
|
Machine Translation (Q)
|
57% |
293
7.15 IPS |
