samsung SM-X820
Geekbench ML Score
1196
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 05:08 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X820 |
| Model ID | samsung SM-X820 |
| Motherboard | gts10pwifi |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
666
124.6 IPS |
|
|
Image Classification (F16)
|
100% |
697
130.5 IPS |
|
|
Image Classification (I8)
|
97% |
673
125.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1397
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1675
28.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1625
27.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
761
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
1173
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
1166
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
477
35.6 IPS |
|
|
Object Detection (F16)
|
100% |
639
47.7 IPS |
|
|
Object Detection (I8)
|
62% |
538
40.2 IPS |
|
|
Face Detection (F32)
|
100% |
2370
28.2 IPS |
|
|
Face Detection (F16)
|
98% |
3023
35.9 IPS |
|
|
Face Detection (I8)
|
86% |
2355
28.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1574
12.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2126
16.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2159
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4170
5.49 IPS |
|
|
Style Transfer (F16)
|
100% |
5298
6.97 IPS |
|
|
Style Transfer (I8)
|
98% |
5367
7.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
886
31.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1197
42.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1215
43.4 IPS |
|
|
Text Classification (F32)
|
100% |
462
663.3 IPS |
|
|
Text Classification (F16)
|
100% |
461
661.9 IPS |
|
|
Text Classification (I8)
|
92% |
736
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
716
13.2 IPS |
|
|
Machine Translation (F16)
|
100% |
695
12.8 IPS |
|
|
Machine Translation (I8)
|
64% |
739
13.6 IPS |
