Samsung Galaxy Note10+
Geekbench AI Score
299
Single Precision Score
299
Half Precision Score
577
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | March 01 2025 03:55 AM |
| Views | 3 |
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% |
169
31.5 IPS |
|
|
Image Classification (HP)
|
100% |
163
30.3 IPS |
|
|
Image Classification (Q)
|
100% |
429
79.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
167
2.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
180
2.92 IPS |
|
|
Image Segmentation (Q)
|
98% |
509
8.27 IPS |
|
|
Pose Estimation (SP)
|
100% |
656
0.76 IPS |
|
|
Pose Estimation (HP)
|
100% |
641
0.75 IPS |
|
|
Pose Estimation (Q)
|
84% |
1158
1.37 IPS |
|
|
Object Detection (SP)
|
100% |
145
11.5 IPS |
|
|
Object Detection (HP)
|
100% |
145
11.5 IPS |
|
|
Object Detection (Q)
|
83% |
379
30.6 IPS |
|
|
Face Detection (SP)
|
100% |
358
4.26 IPS |
|
|
Face Detection (HP)
|
100% |
364
4.33 IPS |
|
|
Face Detection (Q)
|
95% |
807
9.63 IPS |
|
|
Depth Estimation (SP)
|
100% |
519
4.00 IPS |
|
|
Depth Estimation (HP)
|
99% |
520
4.01 IPS |
|
|
Depth Estimation (Q)
|
64% |
961
8.80 IPS |
|
|
Style Transfer (SP)
|
89% |
1099
1.43 IPS |
|
|
Style Transfer (HP)
|
89% |
1085
1.41 IPS |
|
|
Style Transfer (Q)
|
98% |
2470
3.19 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
295
10.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
295
10.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
600
22.2 IPS |
|
|
Text Classification (SP)
|
100% |
140
186.5 IPS |
|
|
Text Classification (HP)
|
100% |
139
186.1 IPS |
|
|
Text Classification (Q)
|
88% |
239
322.0 IPS |
|
|
Machine Translation (SP)
|
100% |
258
4.44 IPS |
|
|
Machine Translation (HP)
|
100% |
250
4.30 IPS |
|
|
Machine Translation (Q)
|
50% |
157
5.57 IPS |
