Xiaomi Redmi Note 9 Pro
Geekbench AI Score
144
Single Precision Score
276
Half Precision Score
463
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | funskeen |
| Upload Date | December 08 2024 08:30 PM |
| Views | 7 |
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% |
164
30.5 IPS |
|
|
Image Classification (HP)
|
100% |
222
41.2 IPS |
|
|
Image Classification (Q)
|
97% |
433
80.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
200
3.24 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.49 IPS |
|
|
Image Segmentation (Q)
|
98% |
542
8.82 IPS |
|
|
Pose Estimation (SP)
|
100% |
497
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
1156
1.35 IPS |
|
|
Pose Estimation (Q)
|
96% |
3613
4.23 IPS |
|
|
Object Detection (SP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.02 IPS |
|
|
Object Detection (Q)
|
85% |
487
39.2 IPS |
|
|
Face Detection (SP)
|
100% |
339
4.03 IPS |
|
|
Face Detection (HP)
|
100% |
278
3.30 IPS |
|
|
Face Detection (Q)
|
97% |
1297
15.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
295
2.27 IPS |
|
|
Depth Estimation (HP)
|
99% |
237
1.83 IPS |
|
|
Depth Estimation (Q)
|
22% |
91
20.8 IPS |
|
|
Style Transfer (SP)
|
100% |
495
0.64 IPS |
|
|
Style Transfer (HP)
|
100% |
385
0.49 IPS |
|
|
Style Transfer (Q)
|
98% |
1849
2.38 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
288
10.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
535
19.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1628
60.3 IPS |
|
|
Text Classification (SP)
|
71% |
2
2.86 IPS |
|
|
Text Classification (HP)
|
100% |
161
214.8 IPS |
|
|
Text Classification (Q)
|
93% |
35
46.9 IPS |
|
|
Machine Translation (SP)
|
100% |
55
0.95 IPS |
|
|
Machine Translation (HP)
|
100% |
265
4.56 IPS |
|
|
Machine Translation (Q)
|
54% |
90
2.54 IPS |
