samsung SM-X810
Geekbench ML Score
268
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 04:06 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X810 |
| Model ID | samsung SM-X810 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
193
36.1 IPS |
|
|
Image Classification (F16)
|
100% |
54
10.0 IPS |
|
|
Image Classification (I8)
|
97% |
81
15.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
441
7.37 IPS |
|
|
Image Segmentation (F16)
|
100% |
429
7.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
240
4.01 IPS |
|
|
Pose Estimation (F32)
|
100% |
632
0.77 IPS |
|
|
Pose Estimation (F16)
|
100% |
702
0.85 IPS |
|
|
Pose Estimation (I8)
|
100% |
2873
3.48 IPS |
|
|
Object Detection (F32)
|
100% |
43
3.21 IPS |
|
|
Object Detection (F16)
|
100% |
93
6.98 IPS |
|
|
Object Detection (I8)
|
61% |
36
2.69 IPS |
|
|
Face Detection (F32)
|
100% |
244
2.90 IPS |
|
|
Face Detection (F16)
|
100% |
197
2.35 IPS |
|
|
Face Detection (I8)
|
86% |
1046
12.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
312
2.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
267
2.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
348
2.70 IPS |
|
|
Style Transfer (F32)
|
100% |
1269
1.67 IPS |
|
|
Style Transfer (F16)
|
100% |
1228
1.62 IPS |
|
|
Style Transfer (I8)
|
98% |
2354
3.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
199
7.10 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
194
6.92 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
285
10.2 IPS |
|
|
Text Classification (F32)
|
100% |
130
186.9 IPS |
|
|
Text Classification (F16)
|
100% |
104
148.9 IPS |
|
|
Text Classification (I8)
|
92% |
33
46.9 IPS |
|
|
Machine Translation (F32)
|
100% |
443
8.15 IPS |
|
|
Machine Translation (F16)
|
100% |
311
5.72 IPS |
|
|
Machine Translation (I8)
|
64% |
286
5.27 IPS |
