Xiaomi Redmi Note 9 Pro
Geekbench AI Score
152
Single Precision Score
279
Half Precision Score
494
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | GladOS |
| Upload Date | January 29 2025 07:06 AM |
| Views | 27 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
173
32.2 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.5 IPS |
|
|
Image Classification (Q)
|
97% |
501
93.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
233
3.79 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
595
9.68 IPS |
|
|
Pose Estimation (SP)
|
100% |
493
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
1155
1.35 IPS |
|
|
Pose Estimation (Q)
|
96% |
3618
4.24 IPS |
|
|
Object Detection (SP)
|
100% |
163
12.9 IPS |
|
|
Object Detection (HP)
|
100% |
113
8.99 IPS |
|
|
Object Detection (Q)
|
85% |
519
41.8 IPS |
|
|
Face Detection (SP)
|
100% |
340
4.04 IPS |
|
|
Face Detection (HP)
|
100% |
278
3.31 IPS |
|
|
Face Detection (Q)
|
97% |
1317
15.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
290
2.24 IPS |
|
|
Depth Estimation (HP)
|
99% |
235
1.81 IPS |
|
|
Depth Estimation (Q)
|
22% |
92
21.0 IPS |
|
|
Style Transfer (SP)
|
100% |
496
0.64 IPS |
|
|
Style Transfer (HP)
|
100% |
382
0.49 IPS |
|
|
Style Transfer (Q)
|
98% |
1890
2.44 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
291
10.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
550
20.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1716
63.6 IPS |
|
|
Text Classification (SP)
|
71% |
2
2.98 IPS |
|
|
Text Classification (HP)
|
100% |
162
216.6 IPS |
|
|
Text Classification (Q)
|
93% |
39
52.0 IPS |
|
|
Machine Translation (SP)
|
100% |
73
1.25 IPS |
|
|
Machine Translation (HP)
|
100% |
268
4.61 IPS |
|
|
Machine Translation (Q)
|
54% |
101
2.84 IPS |
