samsung SM-E546B
Geekbench ML Score
418
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 02:29 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-E546B |
| Model ID | samsung SM-E546B |
| Motherboard | s5e8835 |
| 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 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
223
41.7 IPS |
|
|
Image Classification (F16)
|
100% |
236
44.1 IPS |
|
|
Image Classification (I8)
|
97% |
158
29.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
274
4.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
372
6.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
573
9.58 IPS |
|
|
Pose Estimation (F32)
|
100% |
470
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
465
0.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
2441
2.96 IPS |
|
|
Object Detection (F32)
|
100% |
270
20.2 IPS |
|
|
Object Detection (F16)
|
100% |
249
18.6 IPS |
|
|
Object Detection (I8)
|
61% |
869
64.9 IPS |
|
|
Face Detection (F32)
|
100% |
352
4.19 IPS |
|
|
Face Detection (F16)
|
100% |
337
4.00 IPS |
|
|
Face Detection (I8)
|
86% |
621
7.38 IPS |
|
|
Depth Estimation (F32)
|
100% |
413
3.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
400
3.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
683
5.29 IPS |
|
|
Style Transfer (F32)
|
100% |
848
1.12 IPS |
|
|
Style Transfer (F16)
|
100% |
858
1.13 IPS |
|
|
Style Transfer (I8)
|
98% |
2063
2.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
303
10.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
254
9.07 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
843
30.1 IPS |
|
|
Text Classification (F32)
|
100% |
422
607.2 IPS |
|
|
Text Classification (F16)
|
100% |
344
494.5 IPS |
|
|
Text Classification (I8)
|
92% |
309
443.5 IPS |
|
|
Machine Translation (F32)
|
100% |
411
7.56 IPS |
|
|
Machine Translation (F16)
|
100% |
188
3.45 IPS |
|
|
Machine Translation (I8)
|
64% |
104
1.91 IPS |
