Samsung Galaxy M51
Geekbench ML Score
346
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 03 2024 01:45 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Samsung Galaxy M51 |
| Model ID | samsung SM-M515F |
| Motherboard | sm6150 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.40 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
186
34.7 IPS |
|
|
Image Classification (F16)
|
100% |
185
34.7 IPS |
|
|
Image Classification (I8)
|
97% |
315
59.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
252
4.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
258
4.31 IPS |
|
|
Image Segmentation (I8)
|
98% |
268
4.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
352
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1652
2.00 IPS |
|
|
Object Detection (F32)
|
100% |
195
14.6 IPS |
|
|
Object Detection (F16)
|
100% |
195
14.5 IPS |
|
|
Object Detection (I8)
|
61% |
441
32.9 IPS |
|
|
Face Detection (F32)
|
100% |
392
4.66 IPS |
|
|
Face Detection (F16)
|
100% |
394
4.68 IPS |
|
|
Face Detection (I8)
|
86% |
781
9.28 IPS |
|
|
Depth Estimation (F32)
|
100% |
361
2.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
367
2.85 IPS |
|
|
Depth Estimation (I8)
|
95% |
830
6.44 IPS |
|
|
Style Transfer (F32)
|
100% |
561
0.74 IPS |
|
|
Style Transfer (F16)
|
100% |
549
0.72 IPS |
|
|
Style Transfer (I8)
|
98% |
1450
1.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
203
7.27 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
212
7.57 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
593
21.2 IPS |
|
|
Text Classification (F32)
|
100% |
191
275.0 IPS |
|
|
Text Classification (F16)
|
100% |
195
280.7 IPS |
|
|
Text Classification (I8)
|
92% |
160
229.7 IPS |
|
|
Machine Translation (F32)
|
100% |
435
8.01 IPS |
|
|
Machine Translation (F16)
|
100% |
427
7.86 IPS |
|
|
Machine Translation (I8)
|
64% |
145
2.67 IPS |
