Samsung Galaxy Note10+
Geekbench AI Score
152
Single Precision Score
153
Half Precision Score
322
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | March 04 2025 04:40 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 855 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Samsung Galaxy Note10+ |
| Model ID | samsung SM-N975U1 |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 11.17 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
90
16.7 IPS |
|
|
Image Classification (HP)
|
100% |
90
16.7 IPS |
|
|
Image Classification (Q)
|
99% |
208
38.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
118
1.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
120
1.94 IPS |
|
|
Image Segmentation (Q)
|
98% |
200
3.26 IPS |
|
|
Pose Estimation (SP)
|
100% |
162
0.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
164
0.19 IPS |
|
|
Pose Estimation (Q)
|
98% |
598
0.70 IPS |
|
|
Object Detection (SP)
|
100% |
89
7.09 IPS |
|
|
Object Detection (HP)
|
100% |
90
7.15 IPS |
|
|
Object Detection (Q)
|
87% |
234
18.8 IPS |
|
|
Face Detection (SP)
|
100% |
236
2.81 IPS |
|
|
Face Detection (HP)
|
100% |
239
2.84 IPS |
|
|
Face Detection (Q)
|
97% |
458
5.47 IPS |
|
|
Depth Estimation (SP)
|
100% |
201
1.55 IPS |
|
|
Depth Estimation (HP)
|
99% |
202
1.56 IPS |
|
|
Depth Estimation (Q)
|
64% |
445
4.04 IPS |
|
|
Style Transfer (SP)
|
100% |
341
0.44 IPS |
|
|
Style Transfer (HP)
|
100% |
342
0.44 IPS |
|
|
Style Transfer (Q)
|
98% |
977
1.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
96
3.55 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
97
3.57 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
326
12.1 IPS |
|
|
Text Classification (SP)
|
100% |
124
165.1 IPS |
|
|
Text Classification (HP)
|
100% |
123
164.6 IPS |
|
|
Text Classification (Q)
|
91% |
203
273.5 IPS |
|
|
Machine Translation (SP)
|
100% |
227
3.91 IPS |
|
|
Machine Translation (HP)
|
100% |
233
4.02 IPS |
|
|
Machine Translation (Q)
|
57% |
161
3.93 IPS |
