Samsung Galaxy Note10+
Geekbench AI Score
278
Single Precision Score
283
Half Precision Score
558
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 18 2025 05:40 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
146
27.2 IPS |
|
|
Image Classification (HP)
|
100% |
166
30.8 IPS |
|
|
Image Classification (Q)
|
100% |
400
74.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
170
2.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
193
3.12 IPS |
|
|
Image Segmentation (Q)
|
98% |
494
8.03 IPS |
|
|
Pose Estimation (SP)
|
100% |
615
0.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
602
0.70 IPS |
|
|
Pose Estimation (Q)
|
84% |
1149
1.36 IPS |
|
|
Object Detection (SP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (HP)
|
100% |
126
10.0 IPS |
|
|
Object Detection (Q)
|
83% |
365
29.5 IPS |
|
|
Face Detection (SP)
|
100% |
323
3.83 IPS |
|
|
Face Detection (HP)
|
100% |
321
3.82 IPS |
|
|
Face Detection (Q)
|
95% |
745
8.90 IPS |
|
|
Depth Estimation (SP)
|
100% |
477
3.68 IPS |
|
|
Depth Estimation (HP)
|
99% |
478
3.68 IPS |
|
|
Depth Estimation (Q)
|
64% |
933
8.55 IPS |
|
|
Style Transfer (SP)
|
89% |
1081
1.40 IPS |
|
|
Style Transfer (HP)
|
89% |
1082
1.41 IPS |
|
|
Style Transfer (Q)
|
98% |
2383
3.07 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
257
9.47 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
255
9.43 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
590
21.9 IPS |
|
|
Text Classification (SP)
|
100% |
139
185.8 IPS |
|
|
Text Classification (HP)
|
100% |
137
182.6 IPS |
|
|
Text Classification (Q)
|
88% |
232
312.8 IPS |
|
|
Machine Translation (SP)
|
100% |
246
4.24 IPS |
|
|
Machine Translation (HP)
|
100% |
241
4.15 IPS |
|
|
Machine Translation (Q)
|
50% |
156
5.53 IPS |
