Xiaomi Redmi Note 9 Pro
Geekbench AI Score
523
Single Precision Score
522
Half Precision Score
1004
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Teva |
| Upload Date | January 24 2026 09:25 PM |
| Views | 8 |
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% |
238
44.2 IPS |
|
|
Image Classification (HP)
|
100% |
240
44.6 IPS |
|
|
Image Classification (Q)
|
100% |
689
128.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
296
4.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
292
4.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
751
12.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1146
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1128
1.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
1712
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
240
19.0 IPS |
|
|
Object Detection (HP)
|
100% |
237
18.8 IPS |
|
|
Object Detection (Q)
|
83% |
691
55.8 IPS |
|
|
Face Detection (SP)
|
100% |
705
8.38 IPS |
|
|
Face Detection (HP)
|
100% |
710
8.44 IPS |
|
|
Face Detection (Q)
|
95% |
1561
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
950
7.32 IPS |
|
|
Depth Estimation (HP)
|
99% |
902
6.95 IPS |
|
|
Depth Estimation (Q)
|
64% |
1580
14.5 IPS |
|
|
Style Transfer (SP)
|
89% |
1898
2.46 IPS |
|
|
Style Transfer (HP)
|
89% |
1907
2.48 IPS |
|
|
Style Transfer (Q)
|
98% |
3880
5.00 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
491
18.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
489
18.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
970
35.9 IPS |
|
|
Text Classification (SP)
|
100% |
286
382.0 IPS |
|
|
Text Classification (HP)
|
100% |
284
379.5 IPS |
|
|
Text Classification (Q)
|
88% |
539
726.4 IPS |
|
|
Machine Translation (SP)
|
100% |
450
7.75 IPS |
|
|
Machine Translation (HP)
|
100% |
480
8.27 IPS |
|
|
Machine Translation (Q)
|
50% |
342
12.1 IPS |
