samsung SM-M146B
Geekbench ML Score
321
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 07:43 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-M146B |
| Model ID | samsung SM-M146B |
| Motherboard | s5e8535 |
| 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 | 5.34 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
196
36.6 IPS |
|
|
Image Classification (F16)
|
100% |
184
34.4 IPS |
|
|
Image Classification (I8)
|
97% |
444
83.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
267
4.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
221
3.70 IPS |
|
|
Image Segmentation (I8)
|
98% |
298
4.98 IPS |
|
|
Pose Estimation (F32)
|
100% |
402
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
375
0.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
1839
2.23 IPS |
|
|
Object Detection (F32)
|
100% |
231
17.3 IPS |
|
|
Object Detection (F16)
|
100% |
208
15.5 IPS |
|
|
Object Detection (I8)
|
61% |
690
51.5 IPS |
|
|
Face Detection (F32)
|
100% |
348
4.14 IPS |
|
|
Face Detection (F16)
|
100% |
344
4.09 IPS |
|
|
Face Detection (I8)
|
86% |
1047
12.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
380
2.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
374
2.90 IPS |
|
|
Depth Estimation (I8)
|
95% |
1289
9.99 IPS |
|
|
Style Transfer (F32)
|
100% |
555
0.73 IPS |
|
|
Style Transfer (F16)
|
100% |
653
0.86 IPS |
|
|
Style Transfer (I8)
|
98% |
1898
2.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
211
7.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
231
8.24 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
895
32.0 IPS |
|
|
Text Classification (F32)
|
100% |
19
27.9 IPS |
|
|
Text Classification (F16)
|
100% |
345
496.1 IPS |
|
|
Text Classification (I8)
|
92% |
409
587.3 IPS |
|
|
Machine Translation (F32)
|
100% |
91
1.68 IPS |
|
|
Machine Translation (F16)
|
100% |
92
1.70 IPS |
|
|
Machine Translation (I8)
|
64% |
40
0.74 IPS |
