samsung SM-X110
Geekbench ML Score
176
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 22 2024 04:05 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X110 |
| Model ID | samsung SM-X110 |
| Motherboard | gta9wifi |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 3.50 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
93
17.4 IPS |
|
|
Image Classification (F16)
|
100% |
166
31.1 IPS |
|
|
Image Classification (I8)
|
97% |
154
28.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
107
1.79 IPS |
|
|
Image Segmentation (F16)
|
100% |
183
3.06 IPS |
|
|
Image Segmentation (I8)
|
98% |
191
3.18 IPS |
|
|
Pose Estimation (F32)
|
100% |
89
0.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
105
0.13 IPS |
|
|
Pose Estimation (I8)
|
100% |
105
0.13 IPS |
|
|
Object Detection (F32)
|
100% |
67
4.99 IPS |
|
|
Object Detection (F16)
|
100% |
87
6.48 IPS |
|
|
Object Detection (I8)
|
62% |
100
7.43 IPS |
|
|
Face Detection (F32)
|
100% |
307
3.65 IPS |
|
|
Face Detection (F16)
|
98% |
402
4.77 IPS |
|
|
Face Detection (I8)
|
86% |
332
3.95 IPS |
|
|
Depth Estimation (F32)
|
100% |
173
1.34 IPS |
|
|
Depth Estimation (F16)
|
100% |
227
1.76 IPS |
|
|
Depth Estimation (I8)
|
95% |
222
1.72 IPS |
|
|
Style Transfer (F32)
|
100% |
343
0.45 IPS |
|
|
Style Transfer (F16)
|
100% |
479
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
477
0.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
92
3.27 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
141
5.03 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
140
4.99 IPS |
|
|
Text Classification (F32)
|
100% |
148
212.4 IPS |
|
|
Text Classification (F16)
|
100% |
147
211.8 IPS |
|
|
Text Classification (I8)
|
92% |
237
341.2 IPS |
|
|
Machine Translation (F32)
|
100% |
274
5.04 IPS |
|
|
Machine Translation (F16)
|
100% |
272
5.01 IPS |
|
|
Machine Translation (I8)
|
64% |
275
5.07 IPS |
