Xiaomi Mi A2 Lite
Geekbench AI Score
9
Single Precision Score
9
Half Precision Score
5
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 24 2025 07:37 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Mi A2 Lite |
| Model ID | Xiaomi Mi A2 Lite |
| Motherboard | MSM8953 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 8 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 2.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
553.4 IPS |
|
|
Image Classification (HP)
|
0% |
0
541.1 IPS |
|
|
Image Classification (Q)
|
0% |
0
574.0 IPS |
|
|
Image Segmentation (SP)
|
73% |
3348
57.9 IPS |
|
|
Image Segmentation (HP)
|
73% |
1996
34.5 IPS |
|
|
Image Segmentation (Q)
|
73% |
5550
95.9 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
115.7 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
164.9 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
322.1 IPS |
|
|
Object Detection (SP)
|
0% |
0
235.6 IPS |
|
|
Object Detection (HP)
|
0% |
0
183.2 IPS |
|
|
Object Detection (Q)
|
0% |
0
151.7 IPS |
|
|
Face Detection (SP)
|
0% |
0
81.6 IPS |
|
|
Face Detection (HP)
|
0% |
0
84.1 IPS |
|
|
Face Detection (Q)
|
0% |
0
126.1 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
145.6 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
159.3 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
150.0 IPS |
|
|
Style Transfer (SP)
|
32% |
18652
234.0 IPS |
|
|
Style Transfer (HP)
|
32% |
28122
352.7 IPS |
|
|
Style Transfer (Q)
|
0% |
0
1.07 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
350.0 IPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
336.3 IPS |
|
|
Image Super-Resolution (Q)
|
2% |
39
463.5 IPS |
|
|
Text Classification (SP)
|
29% |
80
1.38 KIPS |
|
|
Text Classification (HP)
|
29% |
90
1.55 KIPS |
|
|
Text Classification (Q)
|
29% |
68
1.17 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
1.59 IPS |
|
|
Machine Translation (HP)
|
0% |
0
1.67 IPS |
|
|
Machine Translation (Q)
|
0% |
0
1.31 IPS |
