Xiaomi Redmi Note 9 Pro
Geekbench AI Score
174
Single Precision Score
260
Half Precision Score
258
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | funskeen |
| Upload Date | December 08 2024 10:22 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% |
102
18.9 IPS |
|
|
Image Classification (HP)
|
100% |
160
29.8 IPS |
|
|
Image Classification (Q)
|
97% |
164
30.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
111
1.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
190
3.07 IPS |
|
|
Image Segmentation (Q)
|
98% |
165
2.69 IPS |
|
|
Pose Estimation (SP)
|
100% |
201
0.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
275
0.32 IPS |
|
|
Pose Estimation (Q)
|
95% |
274
0.32 IPS |
|
|
Object Detection (SP)
|
100% |
86
6.81 IPS |
|
|
Object Detection (HP)
|
100% |
123
9.78 IPS |
|
|
Object Detection (Q)
|
89% |
128
10.3 IPS |
|
|
Face Detection (SP)
|
100% |
230
2.73 IPS |
|
|
Face Detection (HP)
|
100% |
408
4.85 IPS |
|
|
Face Detection (Q)
|
97% |
407
4.85 IPS |
|
|
Depth Estimation (SP)
|
100% |
239
1.84 IPS |
|
|
Depth Estimation (HP)
|
99% |
404
3.12 IPS |
|
|
Depth Estimation (Q)
|
62% |
333
3.15 IPS |
|
|
Style Transfer (SP)
|
100% |
473
0.61 IPS |
|
|
Style Transfer (HP)
|
100% |
1012
1.30 IPS |
|
|
Style Transfer (Q)
|
98% |
1004
1.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
118
4.37 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
193
7.13 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
190
7.04 IPS |
|
|
Text Classification (SP)
|
100% |
162
216.7 IPS |
|
|
Text Classification (HP)
|
100% |
163
217.5 IPS |
|
|
Text Classification (Q)
|
91% |
271
364.9 IPS |
|
|
Machine Translation (SP)
|
100% |
265
4.57 IPS |
|
|
Machine Translation (HP)
|
100% |
270
4.66 IPS |
|
|
Machine Translation (Q)
|
57% |
204
5.00 IPS |
