samsung SM-X920
Geekbench ML Score
1198
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 05:06 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X920 |
| Model ID | samsung SM-X920 |
| Motherboard | gts10uwifi |
| 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% |
682
127.6 IPS |
|
|
Image Classification (F16)
|
100% |
713
133.3 IPS |
|
|
Image Classification (I8)
|
97% |
674
126.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1354
22.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1682
28.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1653
27.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
767
0.93 IPS |
|
|
Pose Estimation (F16)
|
100% |
1155
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1152
1.40 IPS |
|
|
Object Detection (F32)
|
100% |
503
37.6 IPS |
|
|
Object Detection (F16)
|
100% |
686
51.2 IPS |
|
|
Object Detection (I8)
|
62% |
573
42.8 IPS |
|
|
Face Detection (F32)
|
100% |
2705
32.2 IPS |
|
|
Face Detection (F16)
|
98% |
2894
34.4 IPS |
|
|
Face Detection (I8)
|
86% |
2390
28.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1590
12.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2251
17.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2127
16.5 IPS |
|
|
Style Transfer (F32)
|
100% |
4046
5.32 IPS |
|
|
Style Transfer (F16)
|
100% |
5370
7.06 IPS |
|
|
Style Transfer (I8)
|
98% |
5219
6.86 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
747
26.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1225
43.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1010
36.1 IPS |
|
|
Text Classification (F32)
|
100% |
464
666.5 IPS |
|
|
Text Classification (F16)
|
100% |
464
666.2 IPS |
|
|
Text Classification (I8)
|
92% |
737
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
729
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
711
13.1 IPS |
|
|
Machine Translation (I8)
|
64% |
752
13.8 IPS |
