samsung SM-M156B
Geekbench ML Score
300
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 22 2024 02:27 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-M156B |
| Model ID | samsung SM-M156B |
| 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 | 7.42 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
115
21.5 IPS |
|
|
Image Classification (F16)
|
100% |
347
65.0 IPS |
|
|
Image Classification (I8)
|
97% |
74
13.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
207
3.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
389
6.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
85
1.42 IPS |
|
|
Pose Estimation (F32)
|
100% |
785
0.95 IPS |
|
|
Pose Estimation (F16)
|
100% |
1781
2.16 IPS |
|
|
Pose Estimation (I8)
|
87% |
1128
1.37 IPS |
|
|
Object Detection (F32)
|
100% |
140
10.4 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.4 IPS |
|
|
Object Detection (I8)
|
51% |
94
7.03 IPS |
|
|
Face Detection (F32)
|
25% |
525
6.24 IPS |
|
|
Face Detection (F16)
|
25% |
758
9.01 IPS |
|
|
Face Detection (I8)
|
87% |
135
1.60 IPS |
|
|
Depth Estimation (F32)
|
100% |
344
2.67 IPS |
|
|
Depth Estimation (F16)
|
74% |
444
3.44 IPS |
|
|
Depth Estimation (I8)
|
93% |
355
2.75 IPS |
|
|
Style Transfer (F32)
|
100% |
649
0.85 IPS |
|
|
Style Transfer (F16)
|
100% |
1165
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1575
2.07 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
348
12.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
734
26.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
440
15.7 IPS |
|
|
Text Classification (F32)
|
100% |
79
113.1 IPS |
|
|
Text Classification (F16)
|
100% |
98
140.6 IPS |
|
|
Text Classification (I8)
|
94% |
83
119.4 IPS |
|
|
Machine Translation (F32)
|
100% |
196
3.61 IPS |
|
|
Machine Translation (F16)
|
100% |
227
4.17 IPS |
|
|
Machine Translation (I8)
|
57% |
162
2.98 IPS |
