Samsung Galaxy S20 FE 5G
Geekbench ML Score
583
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 29 2024 07:47 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S20 FE 5G |
| Model ID | samsung SM-G780G |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
265
49.6 IPS |
|
|
Image Classification (F16)
|
100% |
385
72.1 IPS |
|
|
Image Classification (I8)
|
97% |
390
72.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
345
5.77 IPS |
|
|
Image Segmentation (F16)
|
100% |
669
11.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
659
11.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
476
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
960
1.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
960
1.16 IPS |
|
|
Object Detection (F32)
|
100% |
226
16.9 IPS |
|
|
Object Detection (F16)
|
100% |
324
24.2 IPS |
|
|
Object Detection (I8)
|
62% |
376
28.1 IPS |
|
|
Face Detection (F32)
|
100% |
690
8.21 IPS |
|
|
Face Detection (F16)
|
97% |
1475
17.5 IPS |
|
|
Face Detection (I8)
|
87% |
1541
18.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
588
4.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
1148
8.90 IPS |
|
|
Depth Estimation (I8)
|
95% |
1156
8.97 IPS |
|
|
Style Transfer (F32)
|
100% |
1102
1.45 IPS |
|
|
Style Transfer (F16)
|
100% |
2878
3.79 IPS |
|
|
Style Transfer (I8)
|
98% |
2876
3.78 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
295
10.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
667
23.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
665
23.7 IPS |
|
|
Text Classification (F32)
|
100% |
209
300.1 IPS |
|
|
Text Classification (F16)
|
100% |
208
298.7 IPS |
|
|
Text Classification (I8)
|
92% |
361
519.1 IPS |
|
|
Machine Translation (F32)
|
100% |
353
6.49 IPS |
|
|
Machine Translation (F16)
|
100% |
354
6.51 IPS |
|
|
Machine Translation (I8)
|
64% |
446
8.21 IPS |
