Mi 10 Lite Zoom Xiaomi M2002J9E
Geekbench AI Score
155
Single Precision Score
300
Half Precision Score
645
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | kitsunechan_2525 |
| Upload Date | June 10 2025 01:50 AM |
| Views | 13 |
| Notes | Mi 10 Lite Zoom (8+256) Qualcomm Snapdragon 765G MIUI 13.0.7.0.SJVCNXM |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
179
33.3 IPS |
|
|
Image Classification (HP)
|
100% |
236
44.0 IPS |
|
|
Image Classification (Q)
|
97% |
337
62.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
216
3.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
165
2.68 IPS |
|
|
Image Segmentation (Q)
|
98% |
439
7.14 IPS |
|
|
Pose Estimation (SP)
|
100% |
521
0.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
1284
1.50 IPS |
|
|
Pose Estimation (Q)
|
97% |
6704
7.85 IPS |
|
|
Object Detection (SP)
|
100% |
167
13.2 IPS |
|
|
Object Detection (HP)
|
100% |
122
9.65 IPS |
|
|
Object Detection (Q)
|
85% |
717
57.7 IPS |
|
|
Face Detection (SP)
|
100% |
418
4.97 IPS |
|
|
Face Detection (HP)
|
100% |
304
3.61 IPS |
|
|
Face Detection (Q)
|
97% |
2141
25.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
314
2.42 IPS |
|
|
Depth Estimation (HP)
|
99% |
258
1.99 IPS |
|
|
Depth Estimation (Q)
|
22% |
149
34.1 IPS |
|
|
Style Transfer (SP)
|
100% |
548
0.70 IPS |
|
|
Style Transfer (HP)
|
100% |
423
0.54 IPS |
|
|
Style Transfer (Q)
|
98% |
2283
2.94 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
300
11.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
571
21.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2812
104.2 IPS |
|
|
Text Classification (SP)
|
71% |
2
2.84 IPS |
|
|
Text Classification (HP)
|
100% |
177
236.2 IPS |
|
|
Text Classification (Q)
|
93% |
68
90.8 IPS |
|
|
Machine Translation (SP)
|
100% |
58
1.01 IPS |
|
|
Machine Translation (HP)
|
100% |
291
5.01 IPS |
|
|
Machine Translation (Q)
|
54% |
126
3.56 IPS |
