Xiaomi Mi 10T Lite 5G
Geekbench AI Score
173
Single Precision Score
284
Half Precision Score
610
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 16 2025 10:00 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 750G |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Mi 10T Lite 5G |
| Model ID | Xiaomi M2007J17G |
| Motherboard | gauguin |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.26 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
182
33.9 IPS |
|
|
Image Classification (HP)
|
100% |
244
45.3 IPS |
|
|
Image Classification (Q)
|
97% |
271
50.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
265
4.29 IPS |
|
|
Image Segmentation (HP)
|
100% |
156
2.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
526
8.55 IPS |
|
|
Pose Estimation (SP)
|
100% |
537
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
1238
1.44 IPS |
|
|
Pose Estimation (Q)
|
97% |
4334
5.08 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.6 IPS |
|
|
Object Detection (HP)
|
100% |
115
9.14 IPS |
|
|
Object Detection (Q)
|
85% |
629
50.6 IPS |
|
|
Face Detection (SP)
|
100% |
370
4.40 IPS |
|
|
Face Detection (HP)
|
100% |
286
3.40 IPS |
|
|
Face Detection (Q)
|
97% |
1702
20.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
339
2.62 IPS |
|
|
Depth Estimation (HP)
|
99% |
245
1.89 IPS |
|
|
Depth Estimation (Q)
|
22% |
115
26.4 IPS |
|
|
Style Transfer (SP)
|
100% |
532
0.68 IPS |
|
|
Style Transfer (HP)
|
100% |
390
0.50 IPS |
|
|
Style Transfer (Q)
|
98% |
2526
3.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
314
11.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
577
21.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2021
74.9 IPS |
|
|
Text Classification (SP)
|
71% |
3
3.62 IPS |
|
|
Text Classification (HP)
|
100% |
154
206.1 IPS |
|
|
Text Classification (Q)
|
93% |
116
155.2 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (HP)
|
100% |
264
4.55 IPS |
|
|
Machine Translation (Q)
|
54% |
159
4.48 IPS |
