Xiaomi Redmi 9T
Geekbench AI Score
124
Single Precision Score
190
Half Precision Score
173
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | almaspite |
| Upload Date | February 17 2026 09:49 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 662 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Redmi 9T |
| Model ID | Xiaomi M2010J19SY |
| Motherboard | lemon |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.02 GHz |
| Memory Information | |
|---|---|
| Size | 3.63 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
88
16.4 IPS |
|
|
Image Classification (HP)
|
100% |
143
26.5 IPS |
|
|
Image Classification (Q)
|
99% |
134
25.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
128
2.07 IPS |
|
|
Image Segmentation (HP)
|
100% |
201
3.27 IPS |
|
|
Image Segmentation (Q)
|
98% |
190
3.09 IPS |
|
|
Pose Estimation (SP)
|
100% |
428
0.50 IPS |
|
|
Pose Estimation (HP)
|
99% |
698
0.81 IPS |
|
|
Pose Estimation (Q)
|
97% |
683
0.80 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.69 IPS |
|
|
Object Detection (HP)
|
99% |
111
8.77 IPS |
|
|
Object Detection (Q)
|
85% |
104
8.35 IPS |
|
|
Face Detection (SP)
|
100% |
281
3.34 IPS |
|
|
Face Detection (HP)
|
100% |
435
5.17 IPS |
|
|
Face Detection (Q)
|
97% |
387
4.62 IPS |
|
|
Depth Estimation (SP)
|
100% |
270
2.08 IPS |
|
|
Depth Estimation (HP)
|
98% |
406
3.14 IPS |
|
|
Depth Estimation (Q)
|
63% |
330
3.05 IPS |
|
|
Style Transfer (SP)
|
100% |
640
0.82 IPS |
|
|
Style Transfer (HP)
|
100% |
985
1.27 IPS |
|
|
Style Transfer (Q)
|
98% |
945
1.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
110
4.06 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
165
6.09 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
150
5.56 IPS |
|
|
Text Classification (SP)
|
35% |
5
48.6 IPS |
|
|
Text Classification (HP)
|
35% |
8
72.5 IPS |
|
|
Text Classification (Q)
|
35% |
8
68.2 IPS |
|
|
Machine Translation (SP)
|
100% |
96
1.65 IPS |
|
|
Machine Translation (HP)
|
97% |
125
2.17 IPS |
|
|
Machine Translation (Q)
|
64% |
93
1.92 IPS |
