Xiaomi Redmi 9T
Geekbench AI Score
29
Single Precision Score
89
Half Precision Score
87
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 28 2025 02:03 PM |
| Views | 12 |
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% |
27
5.10 IPS |
|
|
Image Classification (HP)
|
100% |
56
10.4 IPS |
|
|
Image Classification (Q)
|
97% |
57
10.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
27
0.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
91
1.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
91
1.48 IPS |
|
|
Pose Estimation (SP)
|
100% |
48
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
95
0.11 IPS |
|
|
Pose Estimation (Q)
|
95% |
95
0.11 IPS |
|
|
Object Detection (SP)
|
100% |
27
2.17 IPS |
|
|
Object Detection (HP)
|
100% |
46
3.69 IPS |
|
|
Object Detection (Q)
|
89% |
46
3.69 IPS |
|
|
Face Detection (SP)
|
100% |
69
0.82 IPS |
|
|
Face Detection (HP)
|
100% |
171
2.03 IPS |
|
|
Face Detection (Q)
|
97% |
176
2.10 IPS |
|
|
Depth Estimation (SP)
|
100% |
65
0.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
134
1.03 IPS |
|
|
Depth Estimation (Q)
|
62% |
110
1.04 IPS |
|
|
Style Transfer (SP)
|
0
|
||
|
Style Transfer (HP)
|
100% |
255
0.33 IPS |
|
|
Style Transfer (Q)
|
98% |
253
0.33 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
32
1.17 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
68
2.52 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
67
2.50 IPS |
|
|
Text Classification (SP)
|
100% |
41
55.3 IPS |
|
|
Text Classification (HP)
|
100% |
41
55.2 IPS |
|
|
Text Classification (Q)
|
91% |
53
70.6 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.49 IPS |
|
|
Machine Translation (HP)
|
100% |
87
1.49 IPS |
|
|
Machine Translation (Q)
|
57% |
69
1.68 IPS |
