Xiaomi Redmi Note 9 Pro
Geekbench AI Score
524
Single Precision Score
517
Half Precision Score
1002
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | GladOS |
| Upload Date | January 29 2025 07:13 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
228
42.5 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.4 IPS |
|
|
Image Classification (Q)
|
100% |
698
129.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
292
4.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
287
4.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
742
12.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1144
1.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1105
1.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
1712
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
238
18.9 IPS |
|
|
Object Detection (HP)
|
100% |
238
18.9 IPS |
|
|
Object Detection (Q)
|
83% |
692
55.9 IPS |
|
|
Face Detection (SP)
|
100% |
707
8.40 IPS |
|
|
Face Detection (HP)
|
100% |
718
8.53 IPS |
|
|
Face Detection (Q)
|
95% |
1567
18.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
958
7.38 IPS |
|
|
Depth Estimation (HP)
|
99% |
866
6.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
1574
14.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1858
2.41 IPS |
|
|
Style Transfer (HP)
|
89% |
1927
2.50 IPS |
|
|
Style Transfer (Q)
|
98% |
3895
5.02 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
492
18.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
486
18.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
956
35.4 IPS |
|
|
Text Classification (SP)
|
100% |
290
386.8 IPS |
|
|
Text Classification (HP)
|
100% |
284
378.6 IPS |
|
|
Text Classification (Q)
|
88% |
526
709.0 IPS |
|
|
Machine Translation (SP)
|
100% |
481
8.29 IPS |
|
|
Machine Translation (HP)
|
100% |
459
7.90 IPS |
|
|
Machine Translation (Q)
|
50% |
345
12.3 IPS |
