Xiaomi Redmi Note 9 Pro
Geekbench AI Score
524
Single Precision Score
523
Half Precision Score
1003
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | funskeen |
| Upload Date | December 08 2024 07:55 PM |
| Views | 5 |
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% |
235
43.8 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.5 IPS |
|
|
Image Classification (Q)
|
100% |
691
128.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
294
4.77 IPS |
|
|
Image Segmentation (HP)
|
100% |
294
4.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
741
12.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1113
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
1147
1.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
1713
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
231
18.3 IPS |
|
|
Object Detection (HP)
|
100% |
232
18.4 IPS |
|
|
Object Detection (Q)
|
83% |
690
55.7 IPS |
|
|
Face Detection (SP)
|
100% |
715
8.50 IPS |
|
|
Face Detection (HP)
|
100% |
699
8.30 IPS |
|
|
Face Detection (Q)
|
95% |
1556
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
957
7.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
961
7.41 IPS |
|
|
Depth Estimation (Q)
|
64% |
1585
14.5 IPS |
|
|
Style Transfer (SP)
|
89% |
1916
2.49 IPS |
|
|
Style Transfer (HP)
|
89% |
1892
2.46 IPS |
|
|
Style Transfer (Q)
|
98% |
3882
5.01 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
499
18.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
477
17.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
957
35.4 IPS |
|
|
Text Classification (SP)
|
100% |
281
374.7 IPS |
|
|
Text Classification (HP)
|
100% |
287
383.3 IPS |
|
|
Text Classification (Q)
|
88% |
543
732.3 IPS |
|
|
Machine Translation (SP)
|
100% |
484
8.33 IPS |
|
|
Machine Translation (HP)
|
100% |
478
8.24 IPS |
|
|
Machine Translation (Q)
|
50% |
345
12.2 IPS |
