samsung SM-A235F
Geekbench AI Score
36
Single Precision Score
66
Half Precision Score
109
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 21 2024 03:38 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A235F |
| Model ID | samsung SM-A235F |
| Motherboard | bengal |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
31
5.71 IPS |
|
|
Image Classification (HP)
|
100% |
60
11.2 IPS |
|
|
Image Classification (Q)
|
97% |
61
11.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
31
0.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
102
1.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
102
1.65 IPS |
|
|
Pose Estimation (SP)
|
100% |
54
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
105
0.12 IPS |
|
|
Pose Estimation (Q)
|
95% |
105
0.12 IPS |
|
|
Object Detection (SP)
|
100% |
30
2.41 IPS |
|
|
Object Detection (HP)
|
100% |
50
4.00 IPS |
|
|
Object Detection (Q)
|
89% |
50
3.97 IPS |
|
|
Face Detection (SP)
|
100% |
78
0.92 IPS |
|
|
Face Detection (HP)
|
100% |
190
2.26 IPS |
|
|
Face Detection (Q)
|
97% |
195
2.33 IPS |
|
|
Depth Estimation (SP)
|
100% |
73
0.56 IPS |
|
|
Depth Estimation (HP)
|
99% |
148
1.14 IPS |
|
|
Depth Estimation (Q)
|
62% |
120
1.14 IPS |
|
|
Style Transfer (SP)
|
0
|
||
|
Style Transfer (HP)
|
100% |
207
0.27 IPS |
|
|
Style Transfer (Q)
|
98% |
394
0.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55
2.05 IPS |
|
|
Image Super-Resolution (HP)
|
0
|
||
|
Image Super-Resolution (Q)
|
97% |
103
3.83 IPS |
|
|
Text Classification (SP)
|
100% |
70
93.6 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.1 IPS |
|
|
Text Classification (Q)
|
91% |
91
121.8 IPS |
|
|
Machine Translation (SP)
|
100% |
122
2.10 IPS |
|
|
Machine Translation (HP)
|
100% |
122
2.10 IPS |
|
|
Machine Translation (Q)
|
57% |
91
2.24 IPS |
