Xiaomi Redmi Note 9 Pro
Geekbench AI Score
186
Single Precision Score
187
Half Precision Score
410
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | GladOS |
| Upload Date | January 29 2025 11:07 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 720G |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Xiaomi Redmi Note 9 Pro |
| Model ID | Xiaomi Redmi Note 9 Pro |
| Motherboard | joyeuse |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 15 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.32 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
110
20.5 IPS |
|
|
Image Classification (HP)
|
100% |
112
20.8 IPS |
|
|
Image Classification (Q)
|
99% |
266
49.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
153
2.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
280
4.55 IPS |
|
|
Pose Estimation (SP)
|
100% |
205
0.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
206
0.24 IPS |
|
|
Pose Estimation (Q)
|
98% |
771
0.90 IPS |
|
|
Object Detection (SP)
|
100% |
112
8.88 IPS |
|
|
Object Detection (HP)
|
100% |
113
8.95 IPS |
|
|
Object Detection (Q)
|
87% |
299
24.0 IPS |
|
|
Face Detection (SP)
|
100% |
271
3.22 IPS |
|
|
Face Detection (HP)
|
100% |
266
3.16 IPS |
|
|
Face Detection (Q)
|
97% |
550
6.55 IPS |
|
|
Depth Estimation (SP)
|
100% |
234
1.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
234
1.80 IPS |
|
|
Depth Estimation (Q)
|
64% |
544
4.94 IPS |
|
|
Style Transfer (SP)
|
100% |
384
0.49 IPS |
|
|
Style Transfer (HP)
|
100% |
387
0.50 IPS |
|
|
Style Transfer (Q)
|
98% |
1157
1.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
117
4.31 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
117
4.31 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
405
15.0 IPS |
|
|
Text Classification (SP)
|
100% |
169
226.0 IPS |
|
|
Text Classification (HP)
|
100% |
169
226.1 IPS |
|
|
Text Classification (Q)
|
91% |
270
363.0 IPS |
|
|
Machine Translation (SP)
|
100% |
271
4.67 IPS |
|
|
Machine Translation (HP)
|
100% |
277
4.77 IPS |
|
|
Machine Translation (Q)
|
57% |
207
5.05 IPS |
