Xiaomi Redmi Note 9 Pro
Geekbench AI Score
290
Single Precision Score
446
Half Precision Score
407
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Teva |
| Upload Date | January 24 2026 10:45 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
221
41.1 IPS |
|
|
Image Classification (HP)
|
100% |
320
59.6 IPS |
|
|
Image Classification (Q)
|
99% |
297
55.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
335
5.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
531
8.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
464
7.54 IPS |
|
|
Pose Estimation (SP)
|
100% |
1275
1.49 IPS |
|
|
Pose Estimation (HP)
|
99% |
2117
2.47 IPS |
|
|
Pose Estimation (Q)
|
97% |
2078
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
170
13.5 IPS |
|
|
Object Detection (HP)
|
99% |
247
19.6 IPS |
|
|
Object Detection (Q)
|
85% |
232
18.7 IPS |
|
|
Face Detection (SP)
|
100% |
602
7.15 IPS |
|
|
Face Detection (HP)
|
100% |
914
10.9 IPS |
|
|
Face Detection (Q)
|
97% |
827
9.86 IPS |
|
|
Depth Estimation (SP)
|
100% |
716
5.51 IPS |
|
|
Depth Estimation (HP)
|
98% |
1156
8.94 IPS |
|
|
Depth Estimation (Q)
|
63% |
952
8.79 IPS |
|
|
Style Transfer (SP)
|
100% |
1721
2.21 IPS |
|
|
Style Transfer (HP)
|
100% |
3165
4.07 IPS |
|
|
Style Transfer (Q)
|
98% |
3045
3.93 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
469
17.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
458
17.0 IPS |
|
|
Text Classification (SP)
|
35% |
11
107.8 IPS |
|
|
Text Classification (HP)
|
35% |
18
167.9 IPS |
|
|
Text Classification (Q)
|
35% |
18
167.4 IPS |
|
|
Machine Translation (SP)
|
100% |
111
1.91 IPS |
|
|
Machine Translation (HP)
|
97% |
126
2.18 IPS |
|
|
Machine Translation (Q)
|
64% |
97
2.00 IPS |
