samsung SM-M156S
Geekbench ML Score
381
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 19 2025 12:36 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-M156S |
| Model ID | samsung SM-M156S |
| Motherboard | m15x |
| 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 | 5.46 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
176
33.0 IPS |
|
|
Image Classification (F16)
|
100% |
176
33.0 IPS |
|
|
Image Classification (I8)
|
97% |
293
54.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
279
4.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
285
4.77 IPS |
|
|
Image Segmentation (I8)
|
98% |
395
6.59 IPS |
|
|
Pose Estimation (F32)
|
100% |
397
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
398
0.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
1727
2.09 IPS |
|
|
Object Detection (F32)
|
100% |
212
15.8 IPS |
|
|
Object Detection (F16)
|
100% |
214
16.0 IPS |
|
|
Object Detection (I8)
|
61% |
377
28.2 IPS |
|
|
Face Detection (F32)
|
100% |
422
5.02 IPS |
|
|
Face Detection (F16)
|
100% |
424
5.04 IPS |
|
|
Face Detection (I8)
|
86% |
820
9.75 IPS |
|
|
Depth Estimation (F32)
|
100% |
405
3.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
415
3.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
887
6.88 IPS |
|
|
Style Transfer (F32)
|
100% |
632
0.83 IPS |
|
|
Style Transfer (F16)
|
100% |
652
0.86 IPS |
|
|
Style Transfer (I8)
|
98% |
1946
2.56 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
228
8.16 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
239
8.53 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
628
22.4 IPS |
|
|
Text Classification (F32)
|
100% |
215
308.6 IPS |
|
|
Text Classification (F16)
|
100% |
220
316.6 IPS |
|
|
Text Classification (I8)
|
92% |
198
283.9 IPS |
|
|
Machine Translation (F32)
|
100% |
388
7.14 IPS |
|
|
Machine Translation (F16)
|
100% |
381
7.01 IPS |
|
|
Machine Translation (I8)
|
64% |
254
4.67 IPS |
