Xiaomi Redmi Note 9 Pro
Geekbench AI Score
186
Single Precision Score
188
Half Precision Score
411
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | funskeen |
| Upload Date | December 08 2024 09:52 PM |
| Views | 5 |
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% |
111
20.7 IPS |
|
|
Image Classification (HP)
|
100% |
113
21.0 IPS |
|
|
Image Classification (Q)
|
99% |
269
50.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
153
2.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
155
2.51 IPS |
|
|
Image Segmentation (Q)
|
98% |
279
4.54 IPS |
|
|
Pose Estimation (SP)
|
100% |
207
0.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
206
0.24 IPS |
|
|
Pose Estimation (Q)
|
98% |
778
0.91 IPS |
|
|
Object Detection (SP)
|
100% |
113
8.98 IPS |
|
|
Object Detection (HP)
|
100% |
112
8.87 IPS |
|
|
Object Detection (Q)
|
87% |
300
24.0 IPS |
|
|
Face Detection (SP)
|
100% |
266
3.16 IPS |
|
|
Face Detection (HP)
|
100% |
276
3.28 IPS |
|
|
Face Detection (Q)
|
97% |
556
6.63 IPS |
|
|
Depth Estimation (SP)
|
100% |
234
1.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
235
1.81 IPS |
|
|
Depth Estimation (Q)
|
64% |
545
4.95 IPS |
|
|
Style Transfer (SP)
|
100% |
386
0.50 IPS |
|
|
Style Transfer (HP)
|
100% |
388
0.50 IPS |
|
|
Style Transfer (Q)
|
98% |
1158
1.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
116
4.29 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
116
4.29 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
405
15.0 IPS |
|
|
Text Classification (SP)
|
100% |
171
228.6 IPS |
|
|
Text Classification (HP)
|
100% |
171
228.3 IPS |
|
|
Text Classification (Q)
|
91% |
271
363.9 IPS |
|
|
Machine Translation (SP)
|
100% |
272
4.68 IPS |
|
|
Machine Translation (HP)
|
100% |
275
4.74 IPS |
|
|
Machine Translation (Q)
|
57% |
204
4.98 IPS |
