Samsung Galaxy Note20 5G
Geekbench ML Score
555
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | saiht |
| Upload Date | July 25 2024 01:08 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Note20 5G |
| Model ID | samsung SM-N981N |
| 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 @ 3.09 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
192
35.9 IPS |
|
|
Image Classification (F16)
|
100% |
273
51.2 IPS |
|
|
Image Classification (I8)
|
97% |
281
52.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
260
4.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
570
9.52 IPS |
|
|
Image Segmentation (I8)
|
98% |
518
8.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
541
0.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
1076
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
1075
1.30 IPS |
|
|
Object Detection (F32)
|
100% |
240
17.9 IPS |
|
|
Object Detection (F16)
|
100% |
258
19.3 IPS |
|
|
Object Detection (I8)
|
62% |
228
17.0 IPS |
|
|
Face Detection (F32)
|
100% |
750
8.92 IPS |
|
|
Face Detection (F16)
|
97% |
1507
17.9 IPS |
|
|
Face Detection (I8)
|
87% |
1522
18.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
662
5.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
1255
9.73 IPS |
|
|
Depth Estimation (I8)
|
95% |
1254
9.72 IPS |
|
|
Style Transfer (F32)
|
100% |
1221
1.61 IPS |
|
|
Style Transfer (F16)
|
100% |
2876
3.78 IPS |
|
|
Style Transfer (I8)
|
98% |
3125
4.11 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
289
10.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
449
16.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
687
24.5 IPS |
|
|
Text Classification (F32)
|
100% |
224
322.4 IPS |
|
|
Text Classification (F16)
|
100% |
224
322.6 IPS |
|
|
Text Classification (I8)
|
92% |
393
564.3 IPS |
|
|
Machine Translation (F32)
|
100% |
367
6.76 IPS |
|
|
Machine Translation (F16)
|
100% |
370
6.80 IPS |
|
|
Machine Translation (I8)
|
64% |
474
8.72 IPS |
