Samsung Galaxy Note20 5G
Geekbench AI Score
56
Single Precision Score
56
Half Precision Score
136
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | saiht |
| Upload Date | August 16 2024 12:10 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 865+ |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
31
5.74 IPS |
|
|
Image Classification (HP)
|
100% |
31
5.80 IPS |
|
|
Image Classification (Q)
|
97% |
86
16.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
41
0.66 IPS |
|
|
Image Segmentation (Q)
|
98% |
82
1.33 IPS |
|
|
Pose Estimation (SP)
|
100% |
61
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
60
0.07 IPS |
|
|
Pose Estimation (Q)
|
98% |
237
0.28 IPS |
|
|
Object Detection (SP)
|
100% |
32
2.54 IPS |
|
|
Object Detection (HP)
|
100% |
32
2.53 IPS |
|
|
Object Detection (Q)
|
89% |
98
7.87 IPS |
|
|
Face Detection (SP)
|
100% |
75
0.89 IPS |
|
|
Face Detection (HP)
|
100% |
76
0.90 IPS |
|
|
Face Detection (Q)
|
97% |
196
2.34 IPS |
|
|
Depth Estimation (SP)
|
100% |
74
0.57 IPS |
|
|
Depth Estimation (HP)
|
100% |
75
0.58 IPS |
|
|
Depth Estimation (Q)
|
73% |
192
1.57 IPS |
|
|
Style Transfer (SP)
|
100% |
134
0.17 IPS |
|
|
Style Transfer (HP)
|
100% |
131
0.17 IPS |
|
|
Style Transfer (Q)
|
98% |
356
0.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40
1.46 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40
1.47 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
147
5.43 IPS |
|
|
Text Classification (SP)
|
100% |
55
73.8 IPS |
|
|
Text Classification (HP)
|
100% |
56
74.9 IPS |
|
|
Text Classification (Q)
|
91% |
96
128.5 IPS |
|
|
Machine Translation (SP)
|
100% |
83
1.43 IPS |
|
|
Machine Translation (HP)
|
100% |
82
1.42 IPS |
|
|
Machine Translation (Q)
|
57% |
73
1.79 IPS |
