Xiaomi Redmi 9
Geekbench AI Score
87
Single Precision Score
86
Half Precision Score
147
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 15 2025 02:03 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM MT6769T |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi 9 |
| Model ID | Xiaomi Redmi 9 |
| Motherboard | mt6768 |
| CPU Information | |
|---|---|
| Name | ARM MT6769T |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.65 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
51
9.41 IPS |
|
|
Image Classification (HP)
|
100% |
48
8.87 IPS |
|
|
Image Classification (Q)
|
99% |
93
17.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
69
1.12 IPS |
|
|
Image Segmentation (HP)
|
100% |
67
1.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
111
1.80 IPS |
|
|
Pose Estimation (SP)
|
100% |
96
0.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
95
0.11 IPS |
|
|
Pose Estimation (Q)
|
98% |
205
0.24 IPS |
|
|
Object Detection (SP)
|
100% |
49
3.87 IPS |
|
|
Object Detection (HP)
|
100% |
49
3.87 IPS |
|
|
Object Detection (Q)
|
87% |
96
7.67 IPS |
|
|
Face Detection (SP)
|
100% |
124
1.47 IPS |
|
|
Face Detection (HP)
|
100% |
125
1.49 IPS |
|
|
Face Detection (Q)
|
97% |
239
2.85 IPS |
|
|
Depth Estimation (SP)
|
100% |
113
0.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
114
0.87 IPS |
|
|
Depth Estimation (Q)
|
64% |
192
1.74 IPS |
|
|
Style Transfer (SP)
|
100% |
219
0.28 IPS |
|
|
Style Transfer (HP)
|
100% |
219
0.28 IPS |
|
|
Style Transfer (Q)
|
98% |
446
0.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
58
2.15 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
58
2.16 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
121
4.50 IPS |
|
|
Text Classification (SP)
|
100% |
73
97.7 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.6 IPS |
|
|
Text Classification (Q)
|
91% |
104
139.8 IPS |
|
|
Machine Translation (SP)
|
100% |
122
2.11 IPS |
|
|
Machine Translation (HP)
|
100% |
124
2.13 IPS |
|
|
Machine Translation (Q)
|
57% |
92
2.24 IPS |
