Samsung Galaxy Note20 5G
Geekbench ML Score
550
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | saiht |
| Upload Date | July 25 2024 01:22 PM |
| Views | 4 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
288
53.8 IPS |
|
|
Image Classification (F16)
|
100% |
490
91.6 IPS |
|
|
Image Classification (I8)
|
97% |
656
122.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
388
6.49 IPS |
|
|
Image Segmentation (F16)
|
100% |
460
7.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
731
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1521
1.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
5631
6.82 IPS |
|
|
Pose Estimation (I8)
|
100% |
10744
13.0 IPS |
|
|
Object Detection (F32)
|
100% |
341
25.4 IPS |
|
|
Object Detection (F16)
|
99% |
488
36.5 IPS |
|
|
Object Detection (I8)
|
59% |
853
63.6 IPS |
|
|
Face Detection (F32)
|
100% |
930
11.1 IPS |
|
|
Face Detection (F16)
|
97% |
1098
13.1 IPS |
|
|
Face Detection (I8)
|
88% |
3265
38.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
475
3.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
563
4.36 IPS |
|
|
Depth Estimation (I8)
|
82% |
6709
52.0 IPS |
|
|
Style Transfer (F32)
|
100% |
769
1.01 IPS |
|
|
Style Transfer (F16)
|
100% |
811
1.07 IPS |
|
|
Style Transfer (I8)
|
98% |
3456
4.55 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
753
26.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1808
64.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4736
169.1 IPS |
|
|
Text Classification (F32)
|
64% |
2
3.40 IPS |
|
|
Text Classification (F16)
|
64% |
2
3.38 IPS |
|
|
Text Classification (I8)
|
94% |
67
96.3 IPS |
|
|
Machine Translation (F32)
|
100% |
88
1.62 IPS |
|
|
Machine Translation (F16)
|
100% |
239
4.40 IPS |
|
|
Machine Translation (I8)
|
58% |
224
4.12 IPS |
