samsung SC-53D
Geekbench ML Score
446
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 11 2024 03:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SC-53D |
| Model ID | samsung SC-53D |
| Motherboard | s5e8835 |
| 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 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.30 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
239
44.7 IPS |
|
|
Image Classification (F16)
|
100% |
227
42.6 IPS |
|
|
Image Classification (I8)
|
97% |
689
128.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
244
4.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
265
4.43 IPS |
|
|
Image Segmentation (I8)
|
98% |
347
5.80 IPS |
|
|
Pose Estimation (F32)
|
100% |
486
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
471
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
2856
3.46 IPS |
|
|
Object Detection (F32)
|
100% |
220
16.4 IPS |
|
|
Object Detection (F16)
|
100% |
266
19.9 IPS |
|
|
Object Detection (I8)
|
61% |
830
61.9 IPS |
|
|
Face Detection (F32)
|
100% |
324
3.85 IPS |
|
|
Face Detection (F16)
|
100% |
323
3.84 IPS |
|
|
Face Detection (I8)
|
86% |
553
6.58 IPS |
|
|
Depth Estimation (F32)
|
100% |
413
3.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
381
2.96 IPS |
|
|
Depth Estimation (I8)
|
95% |
808
6.26 IPS |
|
|
Style Transfer (F32)
|
100% |
870
1.14 IPS |
|
|
Style Transfer (F16)
|
100% |
857
1.13 IPS |
|
|
Style Transfer (I8)
|
98% |
2304
3.03 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
316
11.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
317
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
920
32.9 IPS |
|
|
Text Classification (F32)
|
100% |
339
486.8 IPS |
|
|
Text Classification (F16)
|
100% |
327
470.1 IPS |
|
|
Text Classification (I8)
|
92% |
426
612.4 IPS |
|
|
Machine Translation (F32)
|
100% |
561
10.3 IPS |
|
|
Machine Translation (F16)
|
100% |
465
8.55 IPS |
|
|
Machine Translation (I8)
|
64% |
84
1.54 IPS |
