samsung SM-A155F
Geekbench ML Score
127
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 10:51 AM |
| Views | 1 |
System Information
| 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 |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
44
8.24 IPS |
|
|
Image Classification (F16)
|
100% |
67
12.6 IPS |
|
|
Image Classification (I8)
|
97% |
89
16.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
158
2.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
136
2.27 IPS |
|
|
Image Segmentation (I8)
|
98% |
153
2.55 IPS |
|
|
Pose Estimation (F32)
|
100% |
216
0.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
226
0.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
934
1.13 IPS |
|
|
Object Detection (F32)
|
100% |
58
4.34 IPS |
|
|
Object Detection (F16)
|
100% |
89
6.67 IPS |
|
|
Object Detection (I8)
|
61% |
96
7.15 IPS |
|
|
Face Detection (F32)
|
100% |
189
2.25 IPS |
|
|
Face Detection (F16)
|
100% |
186
2.22 IPS |
|
|
Face Detection (I8)
|
86% |
413
4.91 IPS |
|
|
Depth Estimation (F32)
|
100% |
205
1.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
209
1.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
319
2.48 IPS |
|
|
Style Transfer (F32)
|
100% |
392
0.52 IPS |
|
|
Style Transfer (F16)
|
100% |
425
0.56 IPS |
|
|
Style Transfer (I8)
|
98% |
1238
1.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
104
3.72 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
99
3.54 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
197
7.04 IPS |
|
|
Text Classification (F32)
|
100% |
28
40.2 IPS |
|
|
Text Classification (F16)
|
100% |
15
21.6 IPS |
|
|
Text Classification (I8)
|
92% |
16
23.6 IPS |
|
|
Machine Translation (F32)
|
100% |
48
0.88 IPS |
|
|
Machine Translation (F16)
|
100% |
47
0.86 IPS |
|
|
Machine Translation (I8)
|
64% |
58
1.07 IPS |
