Samsung Galaxy Note10 Lite
Geekbench AI Score
18
Single Precision Score
18
Half Precision Score
9
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 27 2025 06:24 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 9810 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Note10 Lite |
| Model ID | samsung SM-N770F |
| Motherboard | exynos9810 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 2 revision 0 |
| Base Frequency | 1.79 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 4 Cores @ 2.70 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
5.18 KIPS |
|
|
Image Classification (HP)
|
0% |
0
5.15 KIPS |
|
|
Image Classification (Q)
|
0% |
0
5.10 KIPS |
|
|
Image Segmentation (SP)
|
73% |
19171
331.3 IPS |
|
|
Image Segmentation (HP)
|
73% |
19255
332.8 IPS |
|
|
Image Segmentation (Q)
|
73% |
45423
785.0 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
1.26 KIPS |
|
|
Pose Estimation (HP)
|
0% |
0
1.29 KIPS |
|
|
Pose Estimation (Q)
|
0% |
0
4.37 KIPS |
|
|
Object Detection (SP)
|
0% |
0
2.17 KIPS |
|
|
Object Detection (HP)
|
0% |
0
2.14 KIPS |
|
|
Object Detection (Q)
|
0% |
0
1.51 KIPS |
|
|
Face Detection (SP)
|
0% |
0
478.8 IPS |
|
|
Face Detection (HP)
|
0% |
0
474.8 IPS |
|
|
Face Detection (Q)
|
0% |
0
887.4 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
1.63 KIPS |
|
|
Depth Estimation (HP)
|
0% |
0
1.60 KIPS |
|
|
Depth Estimation (Q)
|
0% |
0
1.30 KIPS |
|
|
Style Transfer (SP)
|
32% |
256591
3.22 KIPS |
|
|
Style Transfer (HP)
|
32% |
261122
3.28 KIPS |
|
|
Style Transfer (Q)
|
0% |
0
9.48 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
3.56 KIPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
3.60 KIPS |
|
|
Image Super-Resolution (Q)
|
2% |
373
4.40 KIPS |
|
|
Text Classification (SP)
|
29% |
740
12.8 KIPS |
|
|
Text Classification (HP)
|
29% |
729
12.6 KIPS |
|
|
Text Classification (Q)
|
29% |
523
9.03 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
9.81 IPS |
|
|
Machine Translation (HP)
|
0% |
0
9.65 IPS |
|
|
Machine Translation (Q)
|
0% |
0
4.94 IPS |
