samsung SM-X200
Geekbench ML Score
353
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 24 2024 05:50 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
182
34.0 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.7 IPS |
|
|
Image Classification (I8)
|
97% |
350
65.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
242
4.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
242
4.04 IPS |
|
|
Image Segmentation (I8)
|
98% |
318
5.31 IPS |
|
|
Pose Estimation (F32)
|
100% |
300
0.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
298
0.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
1524
1.85 IPS |
|
|
Object Detection (F32)
|
100% |
189
14.1 IPS |
|
|
Object Detection (F16)
|
100% |
191
14.3 IPS |
|
|
Object Detection (I8)
|
61% |
392
29.3 IPS |
|
|
Face Detection (F32)
|
100% |
375
4.45 IPS |
|
|
Face Detection (F16)
|
100% |
371
4.41 IPS |
|
|
Face Detection (I8)
|
86% |
853
10.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
310
2.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
366
2.84 IPS |
|
|
Depth Estimation (I8)
|
95% |
817
6.33 IPS |
|
|
Style Transfer (F32)
|
100% |
486
0.64 IPS |
|
|
Style Transfer (F16)
|
100% |
525
0.69 IPS |
|
|
Style Transfer (I8)
|
98% |
1506
1.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
221
7.88 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
220
7.86 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
767
27.4 IPS |
|
|
Text Classification (F32)
|
100% |
277
398.2 IPS |
|
|
Text Classification (F16)
|
100% |
283
406.3 IPS |
|
|
Text Classification (I8)
|
92% |
216
310.4 IPS |
|
|
Machine Translation (F32)
|
100% |
349
6.41 IPS |
|
|
Machine Translation (F16)
|
100% |
359
6.60 IPS |
|
|
Machine Translation (I8)
|
64% |
208
3.84 IPS |
