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 03 2025 03:44 PM |
| Views | 4 |
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% |
206
38.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
119
1.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
120
1.94 IPS |
|
|
Image Segmentation (Q)
|
98% |
201
3.27 IPS |
|
|
Pose Estimation (SP)
|
100% |
162
0.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
162
0.19 IPS |
|
|
Pose Estimation (Q)
|
98% |
595
0.70 IPS |
|
|
Object Detection (SP)
|
100% |
89
7.09 IPS |
|
|
Object Detection (HP)
|
100% |
90
7.15 IPS |
|
|
Object Detection (Q)
|
87% |
235
18.9 IPS |
|
|
Face Detection (SP)
|
100% |
236
2.81 IPS |
|
|
Face Detection (HP)
|
100% |
239
2.85 IPS |
|
|
Face Detection (Q)
|
97% |
451
5.38 IPS |
|
|
Depth Estimation (SP)
|
100% |
202
1.55 IPS |
|
|
Depth Estimation (HP)
|
99% |
203
1.56 IPS |
|
|
Depth Estimation (Q)
|
64% |
446
4.05 IPS |
|
|
Style Transfer (SP)
|
100% |
341
0.44 IPS |
|
|
Style Transfer (HP)
|
100% |
341
0.44 IPS |
|
|
Style Transfer (Q)
|
98% |
974
1.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
96
3.56 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
96
3.56 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
325
12.0 IPS |
|
|
Text Classification (SP)
|
100% |
125
166.3 IPS |
|
|
Text Classification (HP)
|
100% |
122
163.2 IPS |
|
|
Text Classification (Q)
|
91% |
203
273.1 IPS |
|
|
Machine Translation (SP)
|
100% |
227
3.91 IPS |
|
|
Machine Translation (HP)
|
100% |
232
4.00 IPS |
|
|
Machine Translation (Q)
|
57% |
162
3.97 IPS |
