Xiaomi Redmi Note 9 Pro
Geekbench AI Score
529
Single Precision Score
531
Half Precision Score
981
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | hafizsyawaldi |
| Upload Date | August 31 2024 07:28 AM |
| Views | 21 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi Redmi Note 9 Pro |
| Model ID | Xiaomi Redmi Note 9 Pro |
| Motherboard | atoll |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
237
44.1 IPS |
|
|
Image Classification (HP)
|
100% |
239
44.5 IPS |
|
|
Image Classification (Q)
|
100% |
697
129.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
297
4.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
299
4.85 IPS |
|
|
Image Segmentation (Q)
|
98% |
756
12.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1152
1.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1138
1.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
1708
2.03 IPS |
|
|
Object Detection (SP)
|
100% |
240
19.0 IPS |
|
|
Object Detection (HP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (Q)
|
87% |
702
56.4 IPS |
|
|
Face Detection (SP)
|
100% |
735
8.74 IPS |
|
|
Face Detection (HP)
|
100% |
733
8.71 IPS |
|
|
Face Detection (Q)
|
95% |
1568
18.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
891
6.86 IPS |
|
|
Depth Estimation (HP)
|
100% |
936
7.21 IPS |
|
|
Depth Estimation (Q)
|
75% |
1771
14.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1951
2.53 IPS |
|
|
Style Transfer (HP)
|
89% |
1939
2.52 IPS |
|
|
Style Transfer (Q)
|
98% |
3906
5.04 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
514
19.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
520
19.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
909
33.7 IPS |
|
|
Text Classification (SP)
|
100% |
286
381.2 IPS |
|
|
Text Classification (HP)
|
100% |
281
374.6 IPS |
|
|
Text Classification (Q)
|
88% |
413
556.6 IPS |
|
|
Machine Translation (SP)
|
100% |
478
8.23 IPS |
|
|
Machine Translation (HP)
|
100% |
468
8.07 IPS |
|
|
Machine Translation (Q)
|
50% |
323
11.5 IPS |
