samsung SM-A155F
Geekbench AI Score
208
Single Precision Score
312
Half Precision Score
191
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | October 08 2024 04:59 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A155F |
| Model ID | samsung SM-A155F |
| Motherboard | a15 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
119
22.1 IPS |
|
|
Image Classification (HP)
|
100% |
360
66.9 IPS |
|
|
Image Classification (Q)
|
97% |
45
8.45 IPS |
|
|
Image Segmentation (SP)
|
100% |
222
3.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
146
2.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
85
1.38 IPS |
|
|
Pose Estimation (SP)
|
100% |
770
0.90 IPS |
|
|
Pose Estimation (HP)
|
98% |
1897
2.22 IPS |
|
|
Pose Estimation (Q)
|
70% |
1074
1.37 IPS |
|
|
Object Detection (SP)
|
100% |
138
10.9 IPS |
|
|
Object Detection (HP)
|
100% |
107
8.50 IPS |
|
|
Object Detection (Q)
|
80% |
84
6.82 IPS |
|
|
Face Detection (SP)
|
28% |
35
6.46 IPS |
|
|
Face Detection (HP)
|
100% |
281
3.34 IPS |
|
|
Face Detection (Q)
|
97% |
131
1.56 IPS |
|
|
Depth Estimation (SP)
|
100% |
348
2.68 IPS |
|
|
Depth Estimation (HP)
|
99% |
238
1.84 IPS |
|
|
Depth Estimation (Q)
|
57% |
246
2.68 IPS |
|
|
Style Transfer (SP)
|
100% |
690
0.89 IPS |
|
|
Style Transfer (HP)
|
100% |
399
0.51 IPS |
|
|
Style Transfer (Q)
|
98% |
1612
2.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
347
12.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
736
27.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
396
14.7 IPS |
|
|
Text Classification (SP)
|
100% |
87
115.5 IPS |
|
|
Text Classification (HP)
|
100% |
158
211.4 IPS |
|
|
Text Classification (Q)
|
93% |
87
117.2 IPS |
|
|
Machine Translation (SP)
|
100% |
216
3.73 IPS |
|
|
Machine Translation (HP)
|
100% |
271
4.66 IPS |
|
|
Machine Translation (Q)
|
55% |
105
2.78 IPS |
