samsung SM-X115
Geekbench ML Score
183
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 10 2024 07:25 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X115 |
| Model ID | samsung SM-X115 |
| Motherboard | gta9 |
| 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 | 3.53 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
93
17.3 IPS |
|
|
Image Classification (F16)
|
100% |
163
30.4 IPS |
|
|
Image Classification (I8)
|
97% |
152
28.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
122
2.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
209
3.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
214
3.58 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% |
79
5.89 IPS |
|
|
Object Detection (F16)
|
100% |
129
9.62 IPS |
|
|
Object Detection (I8)
|
62% |
116
8.69 IPS |
|
|
Face Detection (F32)
|
100% |
276
3.28 IPS |
|
|
Face Detection (F16)
|
98% |
395
4.70 IPS |
|
|
Face Detection (I8)
|
86% |
376
4.47 IPS |
|
|
Depth Estimation (F32)
|
100% |
174
1.35 IPS |
|
|
Depth Estimation (F16)
|
100% |
225
1.75 IPS |
|
|
Depth Estimation (I8)
|
95% |
225
1.74 IPS |
|
|
Style Transfer (F32)
|
100% |
344
0.45 IPS |
|
|
Style Transfer (F16)
|
100% |
478
0.63 IPS |
|
|
Style Transfer (I8)
|
98% |
478
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% |
141
5.03 IPS |
|
|
Text Classification (F32)
|
100% |
146
209.6 IPS |
|
|
Text Classification (F16)
|
100% |
147
211.5 IPS |
|
|
Text Classification (I8)
|
92% |
234
336.9 IPS |
|
|
Machine Translation (F32)
|
100% |
274
5.04 IPS |
|
|
Machine Translation (F16)
|
100% |
270
4.97 IPS |
|
|
Machine Translation (I8)
|
64% |
274
5.05 IPS |
