samsung SM-X820
Geekbench ML Score
1191
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 05:06 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% |
685
128.2 IPS |
|
|
Image Classification (F16)
|
100% |
729
136.4 IPS |
|
|
Image Classification (I8)
|
97% |
664
124.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1407
23.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1723
28.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1584
26.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
763
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
1159
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1157
1.40 IPS |
|
|
Object Detection (F32)
|
100% |
417
31.1 IPS |
|
|
Object Detection (F16)
|
100% |
569
42.5 IPS |
|
|
Object Detection (I8)
|
62% |
568
42.4 IPS |
|
|
Face Detection (F32)
|
100% |
2661
31.6 IPS |
|
|
Face Detection (F16)
|
98% |
2637
31.4 IPS |
|
|
Face Detection (I8)
|
86% |
2934
34.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1554
12.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2272
17.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2154
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4075
5.36 IPS |
|
|
Style Transfer (F16)
|
100% |
5199
6.84 IPS |
|
|
Style Transfer (I8)
|
98% |
5226
6.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
747
26.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1207
43.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1220
43.6 IPS |
|
|
Text Classification (F32)
|
100% |
461
662.3 IPS |
|
|
Text Classification (F16)
|
100% |
460
661.4 IPS |
|
|
Text Classification (I8)
|
92% |
737
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
714
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
692
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
738
13.6 IPS |
