samsung SM-A256B
Geekbench ML Score
254
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 27 2024 04:25 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A256B |
| Model ID | samsung SM-A256B |
| Motherboard | s5e8825 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
178
33.2 IPS |
|
|
Image Classification (F16)
|
100% |
178
33.4 IPS |
|
|
Image Classification (I8)
|
97% |
344
64.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
248
4.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
196
3.27 IPS |
|
|
Image Segmentation (I8)
|
98% |
219
3.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
363
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
358
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
2065
2.50 IPS |
|
|
Object Detection (F32)
|
100% |
222
16.6 IPS |
|
|
Object Detection (F16)
|
100% |
142
10.6 IPS |
|
|
Object Detection (I8)
|
61% |
89
6.63 IPS |
|
|
Face Detection (F32)
|
100% |
256
3.04 IPS |
|
|
Face Detection (F16)
|
100% |
247
2.94 IPS |
|
|
Face Detection (I8)
|
86% |
273
3.24 IPS |
|
|
Depth Estimation (F32)
|
100% |
284
2.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
299
2.32 IPS |
|
|
Depth Estimation (I8)
|
95% |
340
2.64 IPS |
|
|
Style Transfer (F32)
|
100% |
665
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
671
0.88 IPS |
|
|
Style Transfer (I8)
|
98% |
1739
2.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
155
5.54 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
177
6.33 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
177
6.31 IPS |
|
|
Text Classification (F32)
|
100% |
369
530.4 IPS |
|
|
Text Classification (F16)
|
100% |
263
378.1 IPS |
|
|
Text Classification (I8)
|
92% |
213
306.2 IPS |
|
|
Machine Translation (F32)
|
100% |
339
6.24 IPS |
|
|
Machine Translation (F16)
|
100% |
45
0.82 IPS |
|
|
Machine Translation (I8)
|
64% |
27
0.50 IPS |
