samsung SM-A356B
Geekbench ML Score
440
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | kszycho |
| Upload Date | September 18 2024 12:08 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A356B |
| Model ID | samsung SM-A356B |
| 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% |
227
42.5 IPS |
|
|
Image Classification (F16)
|
100% |
241
45.1 IPS |
|
|
Image Classification (I8)
|
97% |
338
63.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
341
5.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
369
6.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
538
8.99 IPS |
|
|
Pose Estimation (F32)
|
100% |
482
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
466
0.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
2610
3.16 IPS |
|
|
Object Detection (F32)
|
100% |
309
23.1 IPS |
|
|
Object Detection (F16)
|
100% |
317
23.7 IPS |
|
|
Object Detection (I8)
|
61% |
720
53.8 IPS |
|
|
Face Detection (F32)
|
100% |
403
4.79 IPS |
|
|
Face Detection (F16)
|
100% |
378
4.49 IPS |
|
|
Face Detection (I8)
|
86% |
657
7.82 IPS |
|
|
Depth Estimation (F32)
|
100% |
493
3.82 IPS |
|
|
Depth Estimation (F16)
|
100% |
414
3.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
931
7.22 IPS |
|
|
Style Transfer (F32)
|
100% |
891
1.17 IPS |
|
|
Style Transfer (F16)
|
100% |
880
1.16 IPS |
|
|
Style Transfer (I8)
|
98% |
2277
3.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
378
13.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
349
12.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
784
28.0 IPS |
|
|
Text Classification (F32)
|
100% |
336
482.8 IPS |
|
|
Text Classification (F16)
|
100% |
364
523.3 IPS |
|
|
Text Classification (I8)
|
92% |
304
437.3 IPS |
|
|
Machine Translation (F32)
|
100% |
311
5.73 IPS |
|
|
Machine Translation (F16)
|
100% |
92
1.69 IPS |
|
|
Machine Translation (I8)
|
64% |
110
2.03 IPS |
