samsung SM-X810
Geekbench ML Score
1092
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:11 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
657
122.9 IPS |
|
|
Image Classification (F16)
|
100% |
1032
193.2 IPS |
|
|
Image Classification (I8)
|
99% |
806
150.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
908
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1000
16.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
988
16.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
969
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1392
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
1385
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
361
27.0 IPS |
|
|
Object Detection (F16)
|
100% |
425
31.7 IPS |
|
|
Object Detection (I8)
|
62% |
440
32.8 IPS |
|
|
Face Detection (F32)
|
100% |
2241
26.6 IPS |
|
|
Face Detection (F16)
|
97% |
2913
34.6 IPS |
|
|
Face Detection (I8)
|
86% |
2619
31.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1508
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2887
22.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2876
22.3 IPS |
|
|
Style Transfer (F32)
|
100% |
3788
4.98 IPS |
|
|
Style Transfer (F16)
|
100% |
8545
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8533
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
458
16.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
392
14.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
394
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
459
659.2 IPS |
|
|
Text Classification (F16)
|
100% |
462
663.4 IPS |
|
|
Text Classification (I8)
|
92% |
684
982.6 IPS |
|
|
Machine Translation (F32)
|
100% |
716
13.2 IPS |
|
|
Machine Translation (F16)
|
100% |
706
13.0 IPS |
|
|
Machine Translation (I8)
|
64% |
758
14.0 IPS |
