samsung SM-X200
Geekbench ML Score
119
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 24 2024 05:42 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X200 |
| Model ID | samsung SM-X200 |
| Motherboard | ums512_25c10 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM UNISOC |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.40 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
78
14.6 IPS |
|
|
Image Classification (F16)
|
100% |
112
21.0 IPS |
|
|
Image Classification (I8)
|
97% |
109
20.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
110
1.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
158
2.63 IPS |
|
|
Image Segmentation (I8)
|
98% |
152
2.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (F16)
|
100% |
67
0.08 IPS |
|
|
Pose Estimation (I8)
|
100% |
67
0.08 IPS |
|
|
Object Detection (F32)
|
100% |
65
4.86 IPS |
|
|
Object Detection (F16)
|
100% |
89
6.65 IPS |
|
|
Object Detection (I8)
|
62% |
89
6.68 IPS |
|
|
Face Detection (F32)
|
100% |
245
2.91 IPS |
|
|
Face Detection (F16)
|
98% |
339
4.03 IPS |
|
|
Face Detection (I8)
|
86% |
318
3.79 IPS |
|
|
Depth Estimation (F32)
|
100% |
116
0.90 IPS |
|
|
Depth Estimation (F16)
|
100% |
162
1.26 IPS |
|
|
Depth Estimation (I8)
|
95% |
147
1.14 IPS |
|
|
Style Transfer (F32)
|
100% |
205
0.27 IPS |
|
|
Style Transfer (F16)
|
100% |
312
0.41 IPS |
|
|
Style Transfer (I8)
|
98% |
312
0.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
64
2.30 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
88
3.14 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
88
3.16 IPS |
|
|
Text Classification (F32)
|
100% |
67
96.2 IPS |
|
|
Text Classification (F16)
|
100% |
67
96.4 IPS |
|
|
Text Classification (I8)
|
92% |
97
139.9 IPS |
|
|
Machine Translation (F32)
|
100% |
124
2.28 IPS |
|
|
Machine Translation (F16)
|
100% |
124
2.28 IPS |
|
|
Machine Translation (I8)
|
64% |
133
2.44 IPS |
