Xiaomi Redmi Note 10 Lite
Geekbench AI Score
519
Single Precision Score
520
Half Precision Score
997
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 17 2024 07:32 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Redmi Note 10 Lite |
| Model ID | Xiaomi Redmi Note 10 Lite |
| Motherboard | curtana |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 15 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.32 GHz |
| Memory Information | |
|---|---|
| Size | 3.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
220
40.9 IPS |
|
|
Image Classification (HP)
|
100% |
237
44.0 IPS |
|
|
Image Classification (Q)
|
100% |
701
130.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
292
4.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
292
4.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
753
12.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1133
1.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
1135
1.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
1711
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
238
18.9 IPS |
|
|
Object Detection (HP)
|
100% |
238
18.9 IPS |
|
|
Object Detection (Q)
|
83% |
691
55.9 IPS |
|
|
Face Detection (SP)
|
100% |
705
8.38 IPS |
|
|
Face Detection (HP)
|
100% |
706
8.39 IPS |
|
|
Face Detection (Q)
|
95% |
1569
18.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
941
7.25 IPS |
|
|
Depth Estimation (HP)
|
99% |
877
6.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
1572
14.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1839
2.39 IPS |
|
|
Style Transfer (HP)
|
89% |
1906
2.47 IPS |
|
|
Style Transfer (Q)
|
98% |
3888
5.01 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
487
18.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
485
17.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
966
35.8 IPS |
|
|
Text Classification (SP)
|
100% |
289
385.5 IPS |
|
|
Text Classification (HP)
|
100% |
286
382.1 IPS |
|
|
Text Classification (Q)
|
88% |
488
657.7 IPS |
|
|
Machine Translation (SP)
|
100% |
483
8.32 IPS |
|
|
Machine Translation (HP)
|
100% |
479
8.25 IPS |
|
|
Machine Translation (Q)
|
50% |
345
12.2 IPS |
