samsung SM-M346B
Geekbench ML Score
276
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 07 2024 02:23 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-M346B |
| Model ID | samsung SM-M346B |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
118
22.0 IPS |
|
|
Image Classification (F16)
|
100% |
117
22.0 IPS |
|
|
Image Classification (I8)
|
97% |
317
59.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
171
2.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
233
3.89 IPS |
|
|
Image Segmentation (I8)
|
98% |
359
6.00 IPS |
|
|
Pose Estimation (F32)
|
100% |
665
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
1932
2.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
783
0.95 IPS |
|
|
Object Detection (F32)
|
100% |
124
9.24 IPS |
|
|
Object Detection (F16)
|
100% |
124
9.22 IPS |
|
|
Object Detection (I8)
|
61% |
350
26.1 IPS |
|
|
Face Detection (F32)
|
100% |
305
3.63 IPS |
|
|
Face Detection (F16)
|
100% |
305
3.62 IPS |
|
|
Face Detection (I8)
|
86% |
701
8.34 IPS |
|
|
Depth Estimation (F32)
|
100% |
255
1.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
255
1.98 IPS |
|
|
Depth Estimation (I8)
|
95% |
747
5.79 IPS |
|
|
Style Transfer (F32)
|
100% |
549
0.72 IPS |
|
|
Style Transfer (F16)
|
100% |
574
0.75 IPS |
|
|
Style Transfer (I8)
|
98% |
365
0.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
231
8.26 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
303
10.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
451
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
52
74.6 IPS |
|
|
Text Classification (F16)
|
100% |
70
99.9 IPS |
|
|
Text Classification (I8)
|
92% |
42
60.0 IPS |
|
|
Machine Translation (F32)
|
100% |
284
5.22 IPS |
|
|
Machine Translation (F16)
|
100% |
283
5.22 IPS |
|
|
Machine Translation (I8)
|
64% |
381
7.00 IPS |
