Mi 10 Lite Zoom Xiaomi M2002J9E
Geekbench AI Score
532
Single Precision Score
514
Half Precision Score
935
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | kitsunechan_2525 |
| Upload Date | June 10 2025 01:06 AM |
| Views | 14 |
| Notes | Mi 10 Lite Zoom (8+256) Qualcomm Snapdragon 765G MIUI 13.0.7.0.SJVCNXM |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi M2002J9E |
| Model ID | Xiaomi M2002J9E |
| Motherboard | vangogh |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 14 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 1 Core @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
264
49.1 IPS |
|
|
Image Classification (HP)
|
100% |
263
48.9 IPS |
|
|
Image Classification (Q)
|
100% |
689
128.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
315
5.11 IPS |
|
|
Image Segmentation (HP)
|
100% |
314
5.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
772
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1194
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1138
1.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
1693
2.01 IPS |
|
|
Object Detection (SP)
|
100% |
255
20.3 IPS |
|
|
Object Detection (HP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (Q)
|
83% |
692
55.9 IPS |
|
|
Face Detection (SP)
|
100% |
791
9.39 IPS |
|
|
Face Detection (HP)
|
100% |
709
8.42 IPS |
|
|
Face Detection (Q)
|
95% |
1350
16.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
827
6.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
825
6.35 IPS |
|
|
Depth Estimation (Q)
|
64% |
1319
12.1 IPS |
|
|
Style Transfer (SP)
|
89% |
1686
2.19 IPS |
|
|
Style Transfer (HP)
|
89% |
1681
2.18 IPS |
|
|
Style Transfer (Q)
|
98% |
3219
4.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
518
19.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
513
18.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
826
30.6 IPS |
|
|
Text Classification (SP)
|
100% |
253
337.4 IPS |
|
|
Text Classification (HP)
|
100% |
262
349.8 IPS |
|
|
Text Classification (Q)
|
88% |
540
728.6 IPS |
|
|
Machine Translation (SP)
|
100% |
503
8.66 IPS |
|
|
Machine Translation (HP)
|
100% |
433
7.46 IPS |
|
|
Machine Translation (Q)
|
50% |
323
11.5 IPS |
