samsung SM-X210
Geekbench ML Score
261
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | TitanicFreak |
| Upload Date | April 27 2024 06:42 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X210 |
| Model ID | samsung SM-X210 |
| Motherboard | holi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.21 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
112
21.0 IPS |
|
|
Image Classification (F16)
|
100% |
112
21.0 IPS |
|
|
Image Classification (I8)
|
97% |
306
57.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
150
2.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
150
2.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
331
5.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
199
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
199
0.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
765
0.93 IPS |
|
|
Object Detection (F32)
|
100% |
119
8.85 IPS |
|
|
Object Detection (F16)
|
100% |
119
8.87 IPS |
|
|
Object Detection (I8)
|
61% |
343
25.6 IPS |
|
|
Face Detection (F32)
|
100% |
294
3.50 IPS |
|
|
Face Detection (F16)
|
100% |
294
3.49 IPS |
|
|
Face Detection (I8)
|
86% |
658
7.83 IPS |
|
|
Depth Estimation (F32)
|
100% |
254
1.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
254
1.97 IPS |
|
|
Depth Estimation (I8)
|
95% |
742
5.76 IPS |
|
|
Style Transfer (F32)
|
100% |
431
0.57 IPS |
|
|
Style Transfer (F16)
|
100% |
431
0.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1209
1.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
131
4.68 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
131
4.67 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
454
16.2 IPS |
|
|
Text Classification (F32)
|
100% |
152
217.8 IPS |
|
|
Text Classification (F16)
|
100% |
151
217.2 IPS |
|
|
Text Classification (I8)
|
92% |
291
417.7 IPS |
|
|
Machine Translation (F32)
|
100% |
279
5.13 IPS |
|
|
Machine Translation (F16)
|
100% |
279
5.13 IPS |
|
|
Machine Translation (I8)
|
64% |
335
6.16 IPS |
